Consulta: "Artificial intelligence"
Registros recuperados: 64
Data/hora: 12/06/2024 13:55:40

Artificial intelligence in seeding density optimization and yield simulation for oat
Provedor de dados: 91
Autores: Dornelles,Eldair F.; Kraisig,Adriana R.; Silva,José A. G. da; Sawicki,Sandro; Roos-Frantz,Fabricia; Carbonera,Roberto.
ABSTRACT Artificial intelligence may represent an efficient strategy for simulation and optimization of important processes in agriculture. The main goal of the study is to propose the use of artificial intelligence, namely artificial neural networks and genetic algorithms, respectively, in the simulation of oat grain yield and optimization of seeding density, considering the main succession systems of southern Brazil. The study was conducted in a randomized complete block design with four replicates, following a 4 x 2 factorial scheme, for seeding densities (100, 300, 600 and 900 seeds m-2) and oat cultivars (Brisasul and URS Taura), in succession systems of corn/oats and soybean/oats. A multi-layered artificial neural network and a genetic algorithm were...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Avena sativa; Artificial neural networks; Genetic algorithms; Innovation.
Ano: 2018
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662018000300183

Artificial neural networks for sustainable agribusiness: a case study of five energetic crops
Provedor de dados: 115
Autores: Untaru,Mircea; Rotarescu,Vasile; Dorneanu,Liliana.
The growing agricultural economic environment referred to as agribusiness requires continuous balanced cost-benefit solutions. The use of artificial intelligence in this area provides complex solutions that are easily applicable. The objective of this study was to elaborate on innovative instruments from the field of artificial intelligence for the decision-making process related to energetic crops. The field of expertise of this paper is strongly related to current issues of sustainable development. The methodology used is artificial neural networks (ANN) and compares it with other tools. The targeted results regard the optimization of decision-making processes and the forecast of financial results in an agricultural economy. A case study of forecasting...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Energetic crops; Neural networks; Agribusiness; Resource saving.
Ano: 2012
URL: http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1405-31952012000500008

THE USE OF ARTIFICIAL INTELLIGENCE FOR ESTIMATING SOIL RESISTANCE TO PENETRATION
Provedor de dados: 70
Autores: Pereira,Tonismar dos S.; Robaina,Adroaldo D.; Peiter,Marcia X.; Torres,Rogerio R.; Bruning,Jhosefe.
ABSTRACT The aim of this study was to present and to evaluate methodologies for the estimation of soil resistance to penetration (RP) using artificial intelligence prediction techniques. In order to do so, a data base with values of physical-water characteristics of the soils available in the literature was used, and the performances of Artificial Neural Networks (ANN) and Support Vector Machines (SVM) were evaluated. The models generated from the ANNs were implemented through the multilayer perceptron with backpropagation algorithm of Matlab software, varying the number of neurons in the input and intermediate layers. For the procedure from SVM, the RapidMiner software was used, varying input variables, the kernel function and the coefficients of these...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Soil compaction; Machine learning; Support vector machines; Artificial neural networks.
Ano: 2018
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100142

ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF PHYSIOLOGICAL AND PRODUCTIVE VARIABLES OF BROILERS
Provedor de dados: 70
Autores: Abreu,Lucas H. P.; Yanagi Junior,Tadayuki; Bahuti,Marcelo; Hernández-Julio,Yamid F.; Ferraz,Patrícia F. P.
ABSTRACT Due to a number of factors involving the thermal environment of a broiler cutting installation and its interaction with the physiological and productive responses of birds, artificial intelligence has been shown to be an interesting methodology to assist in the decision-making process. For this reason, the main aim of this work was to develop an artificial neural network (ANN) to predict feed conversion (FC), water consumption (Cwater), and cloacal temperature (tclo) of broilers submitted to different air dry-bulb temperatures (24, 27, 30, and 33°C) and durations (1, 2, 3, and 4 days) of thermal stress in the second week of the production cycle. Relative humidity and wind speed were fixed at 60% and 0.2 ms−1, respectively. The experimental data...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Poultry; Thermal stress; Artificial intelligence.
Ano: 2020
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000100001

Predicting chick body mass by artificial intelligence-based models
Provedor de dados: 86
Autores: Ferraz,Patricia Ferreira Ponciano; Yanagi Junior,Tadayuki; Hernández Julio,Yamid Fabián; Castro,Jaqueline de Oliveira; Gates,Richard Stephen; Reis,Gregory Murad; Campos,Alessandro Torres.
The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks) - with the variables dry-bulb air temperature, duration of thermal stress (days), chick age (days), and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro-fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Animal welfare; Artificial neural network; Broiler; Modeling; Neuro-fuzzy network; Thermal comfort.
Ano: 2014
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2014000700559

MULTI AGENT-BASED ENVIRONMENTAL LANDSCAPE (MABEL) - AN ARTIFICIAL INTELLIGENCE SIMULATION MODEL: SOME EARLY ASSESSMENTS
Provedor de dados: 31
Autores: Alexandridis,   Konstantinos T.; Pijanowski,   Bryan C.
The Multi Agent-Based Environmental Landscape model (MABEL) introduces a Distributed Artificial Intelligence (DAI) systemic methodology, to simulate land use and transformation changes over time and space. Computational agents represent abstract relations among geographic, environmental, human and socio-economic variables, with respect to land transformation pattern changes. A multi-agent environment is developed providing task-nonspecific problem-solving abilities,  flexibility on achieving goals and representing existing relations observed in real-world scenarios, and goal-based efficiency. Intelligent MABEL agents acquire spatial expressions and perform specific tasks demonstrating autonomy, environmental interactions, communication and cooperation,...
Tipo: Working or Discussion Paper
Palavras-chave: Environmental Economics and Policy.
Ano: 2002
URL: http://purl.umn.edu/11549

Freshness and quality assessment of parsley using image processing and artificial intelligence techniques
Provedor de dados: 111
Autores: Hosseinpour Zarnaq, Mohammad; Omid, Mahmoud; Soltani Firouz, Mahmoud; Jafarian, Mostafa; Bazyar, Pourya.
Fruits and&amp;nbsp;vegetables&amp;nbsp;are&amp;nbsp;important&amp;nbsp;components of healthy diets. Vegetable freshness is important for both postharvest industry and consumer appeal. This study focused on freshness detection of parsleys using combined image processing and artificial intelligence techniques. A dataset of color and texture features computed from parsley images. Linear discriminant analysis (LDA) and principal component analysis (PCA) methods are used for feature reduction. Multilayer perceptron (MLP) neural networks, support vector machine (SVM) and decision trees (DTs) classifiers were used for classification. Results showed MLP with LDA feature selection methods had higher performance and the overall accuracy, RMSE, MAE of MLP classifier...
Tipo: Info:eu-repo/semantics/article
Ano: 2022
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/7687

Minimizing flight time and fuel consumption for airborne crop spraying
Provedor de dados: 111
Autores: Kamal, Syed Shariq; Jackman, Patrick; Grieve, Bruce.
Abstract: With the world’s growing population and increase in urbanization, the requirement for optimized agriculture has increased.  Agricultural operations such as crop spraying and water management require rigorous monitoring of crops in order to identify the correct time to spray and irrigate the crops.  Thus managing vast properties require an affordable spraying strategy.  Advancement in computer processing speed and algorithms has made it possible to devise such strategies to optimize several agricultural operations.  One of those operations is to spray crops with pesticides and monitor crops.  This requires an airborne vehicle which can monitor and spray crops efficiently.  Several optimization techniques have been used in recent years to optimize...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Crop spraying; Optimisation; Airborne vehicles; Pesticides; Artificial intelligence; United Kingdom.
Ano: 2014
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/2368

Decision support system for the diagnosis of schizophrenia disorders
Provedor de dados: 56
Autores: Razzouk,D.; Mari,J.J.; Shirakawa,I.; Wainer,J.; Sigulem,D.
Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ). The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Clinical decision support systems; Artificial intelligence; Decision making; Expert systems; Schizophrenia; Medical informatics.
Ano: 2006
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2006000100014

Algoritmos no comando das nossas vidas.
Provedor de dados: 14
Autores: LOPES, M. A.
Algoritmos fazem, cada vez mais, parte das nossas vidas, razão por que precisamos entender o que são e as possibilidades que nos oferecem. Esse é um campo do conhecimento que vem alcançando avanços vertiginosos nos últimos anos, a ponto de muitos afirmarem que o futuro pertence aos algoritmos, que estarão no comando de indústrias, do comércio, de veículos autônomos e até de robôs que mimetizarão seres humanos nas mais variadas atividades.
Tipo: Artigo de divulgação na mídia (INFOTECA-E)
Palavras-chave: Inteligência artificial; Análise de Dados; Dado; Tecnologia da Informação; Data analysis; Algorithms; Information technology; Artificial intelligence.
Ano: 2019
URL: http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/1123785

Radar Agtech Brasil 2020/2021: map of the Brazilian startups of the agricultural sector.
Provedor de dados: 14
Brazil leads the way in terms of digitalization in agriculture, and, according to studies conducted by McKinsey, in 2019, the Brazilian agriculturists were, in average, the heaviest users of digital media for their transactions. During the covid-19 pandemic, in 2020, Brazil has grown 10 percentage points, moving from 36% to 46% of agriculturists who use some digital media, surpassing American and European producers who presented a usage rate of 31% and 22%, respectively. The growth of digitalization in agriculture places our country in a distinguished position that can facilitate competitiveness and the future of the agriculture and livestock industry, bringing new tools and approaches to the diversity of Brazilian agriculture and food systems, which have...
Tipo: Livros
Palavras-chave: Agtechs; Agribusiness; Innovation adoption.
Ano: 2022
URL: http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/1143152

Modelo de rastreamento bovino via Smart Contracts com tecnologia Blockchain.
Provedor de dados: 14
Autores: YANO, I. H.; SANTOS, E. H. dos; CASTRO, A. de; BERGIER, I.; SANTOS, P. M.; OLIVEIRA, S. R. de M.; ABREU, U. G. P. de.
Blockchain. Exemplo de rastreamento bovino com Smart Contract. Simulação de rastreamento bovino utilizando Smart Contract. Conclusão.
Tipo: Comunicado Técnico (INFOTECA-E)
Palavras-chave: Blockchain; Cadeia de blocos; Contratos Inteligentes; Rastreamento bovino; Big data; Inteligência artificial; Smart Contract; Artificial intelligence.
Ano: 2018
URL: http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/1101384

A decision network for inspections in organic farms in Italy
Provedor de dados: 21
Autores: Gambelli, Danilo; Zanoli, Raffaele; Solfanelli, Francesco.
Inspections in organic farming systems are the key tool to assure reliability of the organic business and detection of non-compliant operators. Supporting control bodies in the inspection procedure can increase the efficiency and competitiveness of the sector. Here we propose a decision support system for inspections based on Bayesian networks. Our model is based on statistical information taken from the archives of main Italian control body, and considers decision strategies according to the maximization of expected utility based on risk minimization. © 2012 The authors and IOS Press.
Tipo: Journal paper
Palavras-chave: Food security; Food quality and human health Values; Standards and certification.
Ano: 2014
URL: http://orgprints.org/27765/7/27765.pdf

A DSS to improve inspection procedures in organic certification. Evidence from an Italian case study
Provedor de dados: 21
Autores: Gambelli, Danilo; Solfanelli, Francesco; Zanoli, Raffaele.
Inspections in organic farming systems are the key tool to assure reliability of the organic business and detection of non-compliant operators. Supporting control bodies in the inspection procedure can increase the efficiency and competitiveness of the sector. Here we propose a decision support system for inspections based on Bayesian networks. Our model is based on statistical information taken from the archives of main Italian control body, and considers decision strategies according to the maximization of expected utility based on risk minimization.
Tipo: Journal paper
Palavras-chave: Values; Standards and certification Regulation.
Ano: 2014
URL: http://orgprints.org/27762/7/27762.pdf

Descrição do perfil do tronco de árvores em plantios de diferentes espécies por meio de redes neurais artificiais
Provedor de dados: 190
Autores: Campos, Bráulio Pizziôlo Furtado; Silva, Gilson Fernandes da; Binoti, Daniel Henrique Breda; Mendonça, Adriano Ribeiro de; Leite, Helio Garcia.
O objetivo deste trabalho foi analisar a capacidade de uma rede neural artificial (RNA) em descrever o perfil do fuste de árvores de diferentes gêneros e espécies em diferentes condições de crescimento. Para fins comparativos, foram ajustadas equações, empregando-se análise de regressão, para descrever o perfil do tronco. Tanto para as redes neurais quanto para as equações de regressão, a avaliação da acurácia foi realizada com base no coeficiente de correlação entre os diâmetros observados e estimados ao longo do fuste, a raiz quadrada do erro quadrático médio percentual (RMSE) e análise gráfica. Os métodos de inteligência artificial, especialmente RNA, podem ser eficazes em descrever o perfil do fuste de árvores de diferentes espécies em diferentes...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Inventário florestal; Modelos de Crescimento e Produção; Estatística Inventário Florestal; Manejo Florestal; Inteligência artificial Forest inventory; Forest management; Artificial intelligence.
Ano: 2017
URL: http://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/1181

NEURO-FUZZY MODELING OF EYEBALL AND CREST TEMPERATURES IN EGG-LAYING HENS
Provedor de dados: 70
Autores: Lins,Ana C. de S. S.; Lourençoni,Dian; Yanagi Júnior,Tadayuki; Miranda,Isadora B.; Santos,Italo E. dos A.
ABSTRACT Considering the challenges faced by poultry farming, this study aimed to develop a neuro-fuzzy model to predict eyeball and crest temperatures of egg-laying hens based on environmental conditions (dry bulb temperature and relative humidity). To develop the models and simulations, Matlab’s Fuzzy Toolbox® (Anfisedit) was used. Different configurations were used for each of the several neuro-fuzzy models developed. Eyeball temperature (ET) and chicken crest temperature (CCT) were simulated from the developed neuro-fuzzy models, and the obtained results were validated with the variables collected experimentally with the aid of recorder sensors and an infrared thermographic camera. The proposed neuro-fuzzy models allow the accurate estimation of ET and...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Neuro-fuzzy; Thermography; Poultry farming; Simulation; Artificial intelligence.
Ano: 2021
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162021000100034

ESTIMATION OF FUEL CONSUMPTION IN AGRICULTURAL MECHANIZED OPERATIONS USING ARTIFICIAL NEURAL NETWORKS
Provedor de dados: 70
Autores: Borges,Pedro H. M.; Mendoza,Zaíra M. S. H.; Maia,João C. S.; Bianchini,Aloísio; Fernándes,Haroldo C.
ABSTRACT This study aimed to develop artificial neural networks for the estimation of tractor fuel consumption during soil preparation, according to the adopted system. The multilayer perceptron network was chosen. As input data: the soil mechanical penetration resistance, the mobilized area by implements, the working gear and the tractor engine speed. The number of layers and neurons varied to form different architectures. The adjustment was verified based on various statistical criteria. The values estimated by the networks did not differ significantly from those obtained experimentally. The conclusion was that the networks showed adequate reliability and accuracy to predicting the fuel consumption in each tillage system, in function of the input data...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Machine performance; Artificial intelligence; Agricultural planning.
Ano: 2017
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000100136

ARTIFICIAL NEURAL NETWORKS FOR PREDICTING ANIMAL THERMAL COMFORT
Provedor de dados: 70
Autores: Borges,Pedro H. M.; Mendoza,Zaíra M. S. H. de; Morais,Pedro H. M.; Santos,Ronei L. dos.
ABSTRACT The objective of this study was to develop artificial neural networks (ANNs) for predicting animal thermal comfort based on temperature and relative humidity of the air for each day of the year. The data on temperature and relative humidity for a 25-year historical series collected at the Padre Ricardo Remetter Conventional Meteorological Station, located in the city of Santo Antônio de Leverger - Mato Grosso (Brazil), were retrieved from the website of the National Institute of Meteorology. According to the day of the year, the temperature and humidity index was determined as a function of the climatic variables. Therefore, the day of the year was the input variable of the neural networks, and the temperature and humidity index (THI) was the...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Time series; Artificial intelligence; Comfort index.
Ano: 2018
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000600844

PERTINENCE CURVES IN FUZZY MODELING OF THE PRODUCTIVE RESPONSES OF BROILERS
Provedor de dados: 70
Autores: Lourençoni,Dian; Abreu,Paulo G. de; Yanagi Junior,Tadayuki; Campos,Alessandro T.; Yanagi,Silvia de N. M.
ABSTRACT The selection of the type of fuzzy systems pertinence curve allows a better representation of the mathematical model and a smaller simulation error. We aimed to study the effect of pertinence curves in fuzzy modeling of broiler performance, created in different production systems. For the development and testing of fuzzy models, three commercial aviaries (conventional, tunnel with negative pressure, and dark house) were evaluated over one year, totaling six lots per system. For the development of the model, the input variables were enthalpy in each rearing phase (initial: phases 1, 2, and 3; growth: phase 4; and final: phase 5) and the output variables were feed intake (FE), weight gain (GP), feed conversion (FE), and the productive efficiency...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Poultry farming; Production performance; Artificial intelligence; Fuzzy logic.
Ano: 2019
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000300265

PRODUCTIVE RESPONSES FROM BROILER CHICKENS RAISED IN DIFFERENT COMMERCIAL PRODUCTION SYSTEM - PART II: IMPACT OF CLIMATE CHANGE
Provedor de dados: 70
Autores: Lourençoni,Dian; Yanagi Junior,Tadayuki; Yanagi,Silvia de N. M.; Abreu,Paulo G. de; Campos,Alessandro T.
ABSTRACT Broiler chickens are homoeothermic animals, i.e., animals capable of maintaining their body temperature within quite narrow limits; therefore, climate change poses a great challenge to poultry. With this in mind, this research aims to evaluate the performance of broilers submitted to different commercial production systems and exposed to different future scenarios, taking into account the climate change trends. To achieve this objective, we developed and validated a fuzzy model able to predict the performance of a broiler as a function of enthalpy along its life stages. This model was developed and validated in part I of this article based on experimental data collected for one year in three aviaries: conventional, negative pressure, and dark...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Broiler industry; Artificial intelligence; Climate change; Fuzzy system.
Ano: 2019
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100011

FUZZY MODEL FOR PREDICTING CLOACAL TEMPERATURE OF BROILER CHICKENS UNDER THERMAL STRESS
Provedor de dados: 70
Autores: Abreu,Lucas H. P.; Yanagi Junior,Tadayuki; Campos,Alessandro T.; Lourençoni,Dian; Bahuti,Marcelo.
ABSTRACT Broiler chickens submitted to different intensities and durations of thermal stress are subject to variation in cloacal temperature and, consequently, to a decrease in performance. Given the complexity of these interactions, artificial intelligence is a useful methodology for decision-making. Thus, this study aimed to assess and predict, by means of a fuzzy model, the cloacal temperature of broiler chickens submitted to thermal stress in the second week of life, with varying durations and intensities, in climatized wind tunnels. Mamdani's inference and defuzzification methods by means of the center of gravity were used. One hundred and twenty rules were elaborated. The developed fuzzy model was used to predict the cloacal temperature of broiler...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Physiological response; Thermal environment; Mathematical modeling; Fuzzy logic.
Ano: 2019
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100018

PRODUCTIVE RESPONSES FROM BROILER CHICKENS RAISED IN DIFFERENT COMMERCIAL PRODUCTION SYSTEMS - PART I: FUZZY MODELING
Provedor de dados: 70
Autores: Lourençoni,Dian; Yanagi Junior,Tadayuki; Abreu,Paulo G. de; Campos,Alessandro T.; Yanagi,Silvia de N. M.
ABSTRACT Broiler chickens are classified as homoeothermic animals and require a production environment within well-defined thermal comfort intervals. Therefore, the development of algorithms (mathematical models) to control the environment that can be embedded in microcontrollers becomes necessary. Hence, this work aimed to develop a fuzzy model for predicting the productive performance of broiler chickens as a function of the thermal environment during the various breeding phases. The Mamdani inference and defuzzification methods were used, by means of the gravity center, to develop the fuzzy model. Two hundred and forty-three rules with weighting factors of 1.0 each were elaborated. Three commercial warehouses (conventional system, wind tunnel with...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Poultry farming; Productive performance; Artificial intelligence; Fuzzy logic.
Ano: 2019
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000100001

An example of GIS potentiality for coastal zone management: preselection of submerged oyster culture areas near Marennes-Oleron (France)
Provedor de dados: 5
Autores: Durand, H.; Guillaumont, Brigitte; Loarer, Ronan; Loubersac, Lionel; Heral, Maurice; Prou, Jean.
The Charente Maritime coast, in central western France, is the most important area for oyster and mussel production in Europe. High density, in this restricted intertidal area, induces low growing rate and socio-economic difficulties. One of the possible solutions is to shift some oysters from intertidal area to submerged areas. Bathymetry, sedimentology, hydrodynamism, fisheries and administrative rules are some conditions which are considered to establish the better selection of potential zone. The successive steps of setting up the prototype of GIS are presented: digitized traditional data from charts, extracted data from grid models (hydrodynmaic model), merging of thematic covers, proposal of favorable areas. The results are discussed especially on...
Tipo: Text
Palavras-chave: GIS; Modelisation; Bathymetry; Sedimentology; Hydrodynamism; Marennes Oleron.
Ano: 1994
URL: http://archimer.ifremer.fr/doc/00017/12784/9725.pdf

Dissecting the Biological Motherboard (Systems Biology and Beyond)
Provedor de dados: 17
Autores: Abhay Krishna; Ajit Narayanan.
Genome-scale molecular networks, including gene pathways, gene regulatory networks and protein interactions, are central to the investigation of the nascent disciplines of systems biology and bio-complexity. Dissecting these genome-scale molecular networks in its all-possible manifestations is paramount in our quest for a genotype-input phenotype-output application which will also take environment-genome interactions into account.&amp;#xd;&amp;#xa;&amp;#xd;&amp;#xa;Machine learning approaches are now increasingly being used for reverse engineering such networks. Our work stresses the importance of a system approach in biological research and how artificial neural networks are at the forefront of Artificial Intelligence techniques that are increasingly...
Tipo: Presentation
Palavras-chave: Ecology; Bioinformatics.
Ano: 2008
URL: http://precedings.nature.com/documents/2003/version/1

Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee
Provedor de dados: 86
Autores: Silva,Gabi Nunes; Nascimento,Moysés; Sant’Anna,Isabela de Castro; Cruz,Cosme Damião; Caixeta,Eveline Teixeira; Carneiro,Pedro Crescêncio Souza; Rosado,Renato Domiciano Silva; Pestana,Kátia Nogueira; Almeida,Dênia Pires de; Oliveira,Marciane da Silva.
Abstract: The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica). This study used 245 individuals of a F2 population derived from the self-fertilization of the F1 H511-1 hybrid, resulting from a crossing between the susceptible cultivar Catuaí Amarelo IAC 64 (UFV 2148-57) and the resistant parent Híbrido de Timor (UFV 443-03). The 245 individuals were genotyped with 137 markers. Artificial neural networks and Bayesian generalized linear regression analyses were performed. The artificial neural networks were able to identify four important markers belonging to linkage groups that have been recently mapped,...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Coffea arabica; Hemileia vastatrix; Artificial intelligence; Molecular markers; Prediction.
Ano: 2017
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2017000300186

Artificial neural networks, quantile regression, and linear regression for site index prediction in the presence of outliers
Provedor de dados: 86
Autores: Araújo Júnior,Carlos Alberto; Souza,Pábulo Diogo de; Assis,Adriana Leandra de; Cabacinha,Christian Dias; Leite,Helio Garcia; Soares,Carlos Pedro Boechat; Silva,Antonilmar Araújo Lopes da; Castro,Renato Vinícius Oliveira.
Abstract: The objective of this work was to compare methods of obtaining the site index for eucalyptus (Eucalyptus spp.) stands, as well as to evaluate their impact on the stability of this index in databases with and without outliers. Three methods were tested, using linear regression, quantile regression, and artificial neural network. Twenty-two permanent plots from a continuous forest inventory were used, measured in trees with ages from 23 to 83 months. The outliers were identified using a boxplot graphic. The artificial neural network showed better results than the linear and quantile regressions, both for dominant height and site index estimates. The stability obtained for the site index classification by the artificial neural network was also...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Eucalyptus; Artificial intelligence; Dominant height; Forest inventory; Forest modelling; Non-sampling errors.
Ano: 2019
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2019000103200

RESEARCH UPDATES
Provedor de dados: 31
The Importance of Product/Consumer Attributes In Consumer Buying Decisions, by S.M. Fletcher, T.T. Fu, A.V.A. Resurreccion; Supermarket Produce Demand and Shelf Space Effects, by John J. VanSickle, German Molina; Package Size Preference for Meat and Poultry Products As Related to Demographic Characteristics, by Tami J. Gundry, J. Richard Bacon, U.C. Toensmeyer, R. Dean Shippy; Merrimack College to Offer Certificate Program In Food Retail Management, by James J. Corbett; Changes During Freezing, Storage and Stimulated Distribution In Beef Roasts and Ground Beef Intended for Military and School Lunch Program Usage, by B.W. Berry, J.L. Secrist, E.C. Green; Consumer Awareness and Response to Restructured Beef Steaks, by B.W. Berry; Regional Trends and Spacial...
Tipo: Journal Article
Palavras-chave: Research and Development/Tech Change/Emerging Technologies.
Ano: 1988
URL: http://purl.umn.edu/27343

Artificial neural network model for simulation of water distribution in sprinkle irrigation
Provedor de dados: 91
Autores: Menezes,Paulo L. de; Azevedo,Carlos A. V. de; Eyng,Eduardo; Dantas Neto,José; Lima,Vera L. A. de.
ABSTRACTDetermining uniformity coefficients of sprinkle irrigation systems, in general, depends on field trials, which require time and financial resources. One alternative to reduce time and expense is the use of simulations. The objective of this study was to develop an artificial neural network (ANN) to simulate sprinkler precipitation, using the values ​​of operating pressure, wind speed, wind direction and sprinkler nozzle diameter as the input parameters. Field trials were performed with one sprinkler operating in a grid of 16 x 16, collectors with spacing of 1.5 m and different combinations of nozzles, pressures, and wind conditions. The ANN model showed good results in the simulation of precipitation, with Spearman's correlation coefficient (rs)...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Sprinkler; Water distribution uniformity; Artificial intelligence; Computational model.
Ano: 2015
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662015000900817

Automation in accession classification of Brazilian Capsicum germplasm through artificial neural networks
Provedor de dados: 63
Autores: Ferreira,Mariane Gonçalves; Azevedo,Alcinei Mistico; Siman,Luhan Isaac; da Silva,Gustavo Henrique; Carneiro,Clebson dos Santos; Alves,Flávia Maria; Delazari,Fábio Teixeira; da Silva,Derly José Henriques; Nick,Carlos.
ABSTRACT Germplasm classification by species requires specific knowledge on/of the culture of interest. Therefore, efforts aimed at automation of this process are necessary for the efficient management of collections. Automation of germplasm classification through artificial neural networks may be a viable and less laborious strategy. The aims of this study were to verify the classification potential of Capsicum accessions regarding/ the species based on morphological descriptors and artificial neural networks, and to establish the most important descriptors and the best network architecture for this purpose. Five hundred and sixty-four plants from 47 Brazilian Capsicum accessions were evaluated. Neural networks of multilayer perceptron type were used in...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Capsicum spp.; Garson’s method; Artificial intelligence; Taxonomy; Germplasm bank.
Ano: 2017
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162017000300203

Neural networks for predicting breeding values and genetic gains
Provedor de dados: 63
Autores: Silva,Gabi Nunes; Tomaz,Rafael Simões; Sant'Anna,Isabela de Castro; Nascimento,Moysés; Bhering,Leonardo Lopes; Cruz,Cosme Damião.
Analysis using Artificial Neural Networks has been described as an approach in the decision-making process that, although incipient, has been reported as presenting high potential for use in animal and plant breeding. In this study, we introduce the procedure of using the expanded data set for training the network. Wealso proposed using statistical parameters to estimate the breeding value of genotypes in simulated scenarios, in addition to the mean phenotypic value in a feed-forward back propagation multilayer perceptron network. After evaluating artificial neural network configurations, our results showed its superiority to estimates based on linear models, as well as its applicability in the genetic value prediction process. The results further...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Genetic value; Statistics; Simulation; Artificial intelligence; Training strategy.
Ano: 2014
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162014000600008

Multivariate adaptive regression splines (MARS) applied to daily reference evapotranspiration modeling with limited weather data
Provedor de dados: 1
Autores: Ferreira, Lucas Borges; Duarte, Anunciene Barbosa; Cunha, Fernando França da; Fernandes Filho, Elpídio Inácio.
Estimation of reference evapotranspiration (ETo) is very relevant for water resource management. The Penman-Monteith (PM) equation was proposed by the Food and Agriculture Organization (FAO) as the standard method for estimation of ETo. However, this method requires various weather data, such as air temperature, wind speed, solar radiation and relative humidity, which are often unavailable. Thus, the objective of this study was to compare the performance of multivariate adaptive regression splines (MARS) and alternative equations, in their original and calibrated forms, to estimate daily ETo with limited weather data. Daily data from 2002 to 2016 from 8 Brazilian weather stations were used. ETo was estimated using empirical equations, PM equation with...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Data driven; Irrigation scheduling; Agrometeorology; Artificial intelligence.; Agrometeorologia.
Ano: 2019
URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/39880

GenomicLand: Software for genome-wide association studies and genomic prediction
Provedor de dados: 1
Autores: Azevedo, Camila Ferreira; Nascimento, Moysés; Fontes, Vitor Cunha; Silva, Fabyano Fonseca e; Resende, Marcos Deon Vilela de; Cruz, Cosme Damião.
 GenomicLand is free software intended for prediction and genomic association studies based on the R software. This computational tool has an intuitive interface and supports large genomic databases, without requiring the user to use the command line. GenomicLand is available in English, can be downloaded from the Internet (https://licaeufv.wordpress.com/), and requires the Windows or Linux operating system. The software includes statistical procedures based on mixed models, Bayesian inference, dimensionality reduction and artificial intelligence. Examples of data files that can be processed by GenomicLand are available. The examples are useful to learn about the operation of the modules and statistical procedures.
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Statistical analysis; Genomic analysis; Molecular markers; Biometrics.
Ano: 2019
URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/45361

GenomicLand: Software for genome-wide association studies and genomic prediction
Provedor de dados: 1
Autores: Azevedo, Camila Ferreira; Nascimento, Moysés; Fontes, Vitor Cunha; Silva, Fabyano Fonseca e; Resende, Marcos Deon Vilela de; Cruz, Cosme Damião.
 GenomicLand is free software intended for prediction and genomic association studies based on the R software. This computational tool has an intuitive interface and supports large genomic databases, without requiring the user to use the command line. GenomicLand is available in English, can be downloaded from the Internet (https://licaeufv.wordpress.com/), and requires the Windows or Linux operating system. The software includes statistical procedures based on mixed models, Bayesian inference, dimensionality reduction and artificial intelligence. Examples of data files that can be processed by GenomicLand are available. The examples are useful to learn about the operation of the modules and statistical procedures.
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Statistical analysis; Genomic analysis; Molecular markers; Biometrics.
Ano: 2019
URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/45361

Multivariate adaptive regression splines (MARS) applied to daily reference evapotranspiration modeling with limited weather data
Provedor de dados: 1
Autores: Ferreira, Lucas Borges; Duarte, Anunciene Barbosa; Cunha, Fernando França da; Fernandes Filho, Elpídio Inácio.
Estimation of reference evapotranspiration (ETo) is very relevant for water resource management. The Penman-Monteith (PM) equation was proposed by the Food and Agriculture Organization (FAO) as the standard method for estimation of ETo. However, this method requires various weather data, such as air temperature, wind speed, solar radiation and relative humidity, which are often unavailable. Thus, the objective of this study was to compare the performance of multivariate adaptive regression splines (MARS) and alternative equations, in their original and calibrated forms, to estimate daily ETo with limited weather data. Daily data from 2002 to 2016 from 8 Brazilian weather stations were used. ETo was estimated using empirical equations, PM equation with...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: 5.01.05.00-0 data driven; Irrigation scheduling; Agrometeorology; Artificial intelligence. Agrometeorologia.
Ano: 2019
URL: http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/39880

Representing the Human Experts Judgment on Quality Indices of White Rice by Image Processing and Artificial Intelligence Techniques
Provedor de dados: 111
Autores: hosseinzadeh, bahram; Esmaeili, Zahra; Rostami, Sajad; Zareiforoush, Hemad.
In the present study, a grading system based on fuzzy logic was developed to simulate the behavior of an expert in the evaluation and classification of physical properties of rice grains (paddy) for pricing the product. Based on two desired quality indices in this study and the input linguistic variables of fuzzy grading system, 250 samples were prepared with different quality conditions which include all the possible states for the rice grains (paddy). Lighting and imaging were carried out from each 250 samples of rice products in the same condition. Image processing algorithm was conducted to extract geometric features and light intensity of grains and also fuzzy product pricing model was developed in MATLAB software. Fuzzy inference system was designed...
Tipo: Info:eu-repo/semantics/article
Ano: 2016
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/4022

DEVELOPMENT OF AN AUTOMATIC VARIABLE RATE SPRAYING SYSTEM BASED ON CANOPY CHARACTERIZATION USING ARTIFICIAL INTELLIGENCE
Provedor de dados: 111
Autores: Patil, Seema S.; Yuvraj Mahadev Patil; Suhas Bapuso Patil.
Spraying on tree crops must consider the canopy's structural features to maximize its effectiveness. The main drawbacks to VRI technology include the complexity of successfully implementing it and the lack of evidence that it assures better performance in net profit or water savings. Hence, a novel framework based on canopy characterization was presented in this research for an automatic variable-rate spraying system. The first phase was collecting the data, and the next was cleaning it to eliminate redundant information. The pre-treated data are then entered into the Crest- Stride-wise Regression Framework we devised, where we extract the canopy features and evaluate additional parameters. In addition, our proposed model automatically predicts the...
Tipo: Info:eu-repo/semantics/article
Ano: 2024
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/9025

Construction and evaluation of solar system for fuzzy control of intelligent irrigation system
Provedor de dados: 111
Autores: Younesi Alamooti, Mohammad; khafajeh, hamid; Javadi, Arzhang; Dehghanisanij Sanich, Hossein.
Restriction of water resources requires optimal use of agricultural water resources. In this regard, the use of new technologies to increase irrigation efficiency. In arid and extremely arid regions such as Iran, the time and duration of irrigation is the key to achieving sustainable irrigation. Therefore, in this research, after constructing a garden in Imam Khomeini Higher Education Center with an area of ​​500 square meters, and installing equipment related to irrigation and fertilization, a fuzzy control system was designed to optimize water consumption and inputs, intelligent irrigation and fertilization system. The present study presents a practical solution based on artificial intelligence in which all stages of design and implementation are...
Tipo: Info:eu-repo/semantics/article
Ano: 2023
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/8353

Authentication of Virgin Olive Oil by Using Dielectric spectroscopy combined with Some Artificial Intelligence Methods
Provedor de dados: 111
Autores: Soltani, Mahmoud; Rashvand, Mahdi; Teimouri, Nima; Omid, Mahmoud.
Adulteration is a serious problem in the food industry. Olive oil is widely adulterated with other cheap edible oils such as sunflower and canola oils. Therefore, developing a low-cost, practical and rapid analytical method for detecting such adulteration in olive oil would be useful and needed.  In this research, we aimed to develop a dielectric measurement based system combined with complementary analytical intelligent techniques to recognize authentication of virgin olive oil from adulterated with vegetable oils (canola and sunflower). 192 sinusoidal signals in the range of 20 kHz and 20 MHz were feed into the cylindrical dielectric sensor filled with oil sample. Correlation based feature selection (CFS) was applied to select the most appropriate...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Postharvest Engineering Olive oil; Authentication; Dielectric properties; Data mining.
Ano: 2019
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/5483

Modeling of stem form and volume through machine learning
Provedor de dados: 42
Autores: SCHIKOWSKI,ANA B.; CORTE,ANA P.D.; RUZA,MARIELI S.; SANQUETTA,CARLOS R.; MONTAÑO,RAZER A.N.R.
Abstract Taper functions and volume equations are essential for estimation of the individual volume, which have consolidated theory. On the other hand, mathematical innovation is dynamic, and may improve the forestry modeling. The objective was analyzing the accuracy of machine learning (ML) techniques in relation to a volumetric model and a taper function for acácia negra. We used cubing data, and fit equations with Schumacher and Hall volumetric model and with Hradetzky taper function, compared to the algorithms: k nearest neighbor (k-NN), Random Forest (RF) and Artificial Neural Networks (ANN) for estimation of total volume and diameter to the relative height. Models were ranked according to error statistics, as well as their dispersion was verified....
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Artificial intelligence; Data mining; Random forest; ANN.
Ano: 2018
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000703389

Comparison of Regression and Neural Networks Models to Estimate Solar Radiation
Provedor de dados: 117
Autores: Bocco,Mónica; Willington,Enrique; Arias,Mónica.
The incident solar radiation on soil is an important variable used in agricultural applications; it is also relevant in hydrology, meteorology and soil physics, among others. To estimate this variable, empirical models have been developed using several parameters and, recently, prognostic and prediction models based on artificial intelligence techniques such as neural networks. The aim of this work was to develop linear models and neural networks, multilayer perceptron, to estimate daily global solar radiation and compare their efficiency in its application to a region of the Province of Salta, Argentina. Relative sunshine duration, maximum and minimum temperature, rainfall, binary rainfall and extraterrestrial solar radiation data for the period...
Tipo: Journal article
Palavras-chave: Modeling; Prediction; Linear regression; Multilayer perceptron.
Ano: 2010
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392010000300010

Stability of the hypocotyl length of soybean cultivars using neural networks and traditional methods
Provedor de dados: 65
Autores: Alves,Guilherme Ferreira; Nogueira,João Pedro Garcia; Machado Junior,Ronaldo; Ferreira,Silvana da Costa; Nascimento,Moysés; Matsuo,Eder.
ABSTRACT:  The length of the hypocotyl has been highlighted as a potential descriptor of the soybean crop. However, there is no information available in the published literature about its behavior over several planting times. The present study aimed to identify soybean cultivars with stability and predictability of hypocotyl length behavior through neural networks and traditional adaptability and stability methodologies. We analyzed 16 soybean cultivars in 6 planting seasons under greenhouse conditions. In each season, a randomized block design with 4 replications was adopted. The experimental unit was composed of 3 plants. The plot mean was used in the analysis. Hypocotyl length data were analyzed by analysis of variance and Tukey’s test. Then analyses...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Glycine max; Interaction between genotypes and environments; Eberhart-Russell stability analysis artificial intelligence hypocotyl length.
Ano: 2019
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782019000300201

Embedded system in Arduino platform with Fuzzy control to support the grain aeration decision
Provedor de dados: 65
Autores: Szesz Junior,Albino; Monteiro Junior,Marcos; Dias,Ariangelo Hauer; Mathias,Ivo Mário; Conti,Giuvane.
ABSTRACT: Aeration is currently the most commonly used technique to improve the drying and storage of grain, depending on temperature and water content of the grain, as of the temperature and relative humidity of the outside air. In order to monitor temperature and humidity of the grain mass, it is possible to have a network of sensors in the cells of both internal and external storage. Use of artificial intelligence through Fuzzy theory, has been used since the 60s and enables their application on various forms. Thus, it is observed that the aeration of grain in function of representing a system of controlled environment can be studied in relation to the application of this theory. Therefore, the aim of this paper is to present an embedded Fuzzy control...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Arduino; Agriculture; Mathematical model; Fuzzy logic; Grain aeration.
Ano: 2016
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782016001101917

Motif analysis of amphioxus, lamprey and invertebrate estrogen receptors and amphioxus and human estrogen-related receptors: Towards a better understanding of estrogen receptor evolution
Provedor de dados: 17
Autores: Michael E. Baker; Charlie Chandsawangbhuwana.
*Background.*  The origins of steroid-dependent regulation of the vertebrate estrogen receptor (ER) are poorly understood.  Genes with statistically significant sequence similarity to vertebrate ERs have been found in lamprey, a basal vertebrate, and amphioxus, a basal chordate.  Motif analysis of these sequences provides an opportunity to investigate early events in the evolution of the ER.&amp;#xd;&amp;#xa;*Results.*  We used artificial intelligence-based software to construct twelve motifs specific to the estrogen-binding domain of ER[alpha] and ER[beta] in land vertebrates and teleosts.  We mapped these ER-specific motifs onto the sequences of lamprey, amphioxus, invertebrate and selected vertebrate ERs and amphioxus, Ciona and human estrogen-related...
Tipo: Manuscript
Palavras-chave: Cancer; Developmental Biology; Ecology; Evolutionary Biology.
Ano: 2008
URL: http://precedings.nature.com/documents/1542/version/2

Colour reverse learning and animal personalities: the advantage of behavioural diversity assessed with agent-based simulations
Provedor de dados: 17
Autores: Adrian G. Dyer; Alan Dorin; Verena Reinhardt; Marcello G. P. Rosa.
Foraging bees use colour cues to help identify rewarding from unrewarding flowers, but as conditions change, bees may require behavioural flexibility to reverse their learnt preferences. Perceptually similar colours are learnt slowly by honeybees and thus potentially pose a difficult task to reverse-learn. Free-flying honeybees (N = 32) were trained to learn a fine colour discrimination task that could be resolved at ca. 70% accuracy following extended differential conditioning, and were then tested for their ability to reverse-learn this visual problem multiple times. Subsequent analyses identified three different strategies: &amp;#x2018;Deliberative-decisive&amp;#x2019; bees that could, after several flower visits, decisively make a large change to...
Tipo: Manuscript
Palavras-chave: Ecology; Neuroscience.
Ano: 2012
URL: http://precedings.nature.com/documents/7037/version/1

Motif analysis of amphioxus, lamprey and invertebrate estrogen receptors and amphioxus and human estrogen-related receptors: Towards a better understanding of estrogen receptor evolution
Provedor de dados: 17
Autores: Michael E. Baker; Charlie Chandsawangbhuwana.
*Background.*  The origins of steroid-dependent regulation of the vertebrate estrogen receptor (ER) are poorly understood.  Genes with statistically significant sequence similarity to vertebrate ERs have been found in lamprey, a basal vertebrate, and amphioxus, a basal chordate.  Motif analysis of these sequences provides an opportunity to investigate early events in the evolution of the ER.&amp;#xd;&amp;#xa;*Results.*  We used artificial intelligence-based software to construct twelve motifs specific to the estrogen-binding domain of ER[alpha] and ER[beta] in land vertebrates and teleosts.  We mapped these ER-specific motifs onto the sequences of lamprey, amphioxus, invertebrate and selected vertebrate ERs and amphioxus and human estrogen-related receptor...
Tipo: Manuscript
Palavras-chave: Cancer; Developmental Biology; Ecology; Bioinformatics.
Ano: 2008
URL: http://precedings.nature.com/documents/1542/version/1

Smart drying: use of sensors and machine learning for the supervision and control of drying processes
Provedor de dados: 21
Autores: Roberto, Moscetti; Riccardo, Massantini.
Globalization of  market entails the availability of  produces  regardless their production date, pursued through innovation in products and processes to obtain meat, fish and fruit vegetables with improved shelf-life, organoleptic quality, nutritional value, safety and healthiness during the  whole  agrofood  chain.  Consequently,  market  value  of  perishable  commodity  mainly depends  on  the  preservation  method  used  to  guarantee  food  stability  and  thus  to  delay physicochemical,  biochemical  and  microbiological  spoilage.  Among  processing  methods, drying is one of the oldest, typical, effective and viable preservation process throughout the world,  which  allow  to  prevent  food  spoilage  and  decay  through  moisture  removal.  It...
Tipo: Conference paper, poster, etc.
Palavras-chave: "Organics" in general; Food systems.
Ano: 2017
URL: http://orgprints.org/34390/1/Document_8.pdf

Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan
Provedor de dados: 96
Autores: Celik,Senol; Eyduran,Ecevit; Karadas,Koksal; Tariq,Mohammad Masood.
ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF) in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth) and testicular (testicular length, scrotal length, and scrotal circumference) measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1) and with interaction (MARS_2) terms. The superiority...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: ANN; Artificial intelligence; Data mining; Decision tree; MARS algorithm.
Ano: 2017
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982017001100863

NOTA TÉCNICA: PROGRAMA COMPUTACIONAL PARA ESTIMATIVA DAS TEMPERATURAS DO AR NO NORDESTE BRASILEIRO UTILIZANDO REDES NEURAIS ARTIFICIAIS
Provedor de dados: 107
Autores: Moreira, Michel Castro; Cecílio, Roberto Avelino.
A temperatura do ar é um dos fatores mais importantes que afetam a vegetação e controla os processos ecológicos. O objetivo deste trabalho foi desenvolver um programa computacional utilizando redes neurais artificiais para a estimativa da temperatura do ar no Nordeste do Brasil. As arquiteturas, funções de ativação das redes neurias e os parâmetros livres das redes foram definidos para a construção das funções matemáticas que representassem as redes neurais. As funções matemáticas foram implementadas no programa computacional Borland Delphi© 7 com uma interface gráfica para facilitar o uso das redes. O programa computacional desenvolvido foi intitulado netTemperatura NE e permite de forma fácil e rápida estimar as temperaturas mínima, média e máxima do ar...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Meteorologia Agrícola artificial intelligence; Interpolation; GIS; GTOPO30; Climate modeling.
Ano: 2016
URL: http://www.seer.ufv.br/seer/index.php/reveng/article/view/631

Genomic prediction of leaf rust resistance to Arabica coffee using machine learning algorithms
Provedor de dados: 63
Autores: Sousa,Ithalo Coelho de; Nascimento,Moysés; Silva,Gabi Nunes; Nascimento,Ana Carolina Campana; Cruz,Cosme Damião; Silva,Fabyano Fonseca e; Almeida,Dênia Pires de; Pestana,Kátia Nogueira; Azevedo,Camila Ferreira; Zambolim,Laércio; Caixeta,Eveline Teixeira.
ABSTRACT Genomic selection (GS) emphasizes the simultaneous prediction of the genetic effects of thousands of scattered markers over the genome. Several statistical methodologies have been used in GS for the prediction of genetic merit. In general, such methodologies require certain assumptions about the data, such as the normality of the distribution of phenotypic values. To circumvent the non-normality of phenotypic values, the literature suggests the use of Bayesian Generalized Linear Regression (GBLASSO). Another alternative is the models based on machine learning, represented by methodologies such as Artificial Neural Networks (ANN), Decision Trees (DT) and related possible refinements such as Bagging, Random Forest and Boosting. This study aimed to...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Hemileia vastatrix; Statistical learning; Plant breeding; Artificial intelligence.
Ano: 2021
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162021000401102

Artificial neural network for prediction of the area under the disease progress curve of tomato late blight
Provedor de dados: 63
Autores: Alves,Daniel Pedrosa; Tomaz,Rafael Simões; Laurindo,Bruno Soares; Laurindo,Renata Dias Freitas; Silva,Fabyano Fonseca e; Cruz,Cosme Damião; Nick,Carlos; Silva,Derly José Henriques da.
ABSTRACT: Artificial neural networks (ANN) are computational models inspired by the neural systems of living beings capable of learning from examples and using them to solve problems such as non-linear prediction, and pattern recognition, in addition to several other applications. In this study, ANN were used to predict the value of the area under the disease progress curve (AUDPC) for the tomato late blight pathosystem. The AUDPC is widely used by epidemiologic studies of polycyclic diseases, especially those regarding quantitative resistance of genotypes. However, a series of six evaluations over time is necessary to obtain the final area value for this pathosystem. This study aimed to investigate the utilization of ANN to construct an AUDPC in the...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Phytophthora infestans; ANN; AUDPC; Artificial intelligence; Plant breeding.
Ano: 2017
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162017000100051

Improving detection of dairy cow estrus using fuzzy logic
Provedor de dados: 63
Autores: Brunassi,Leandro dos Anjos; Moura,Daniella Jorge de; Nääs,Irenilza de Alencar; Vale,Marcos Martinez do; Souza,Silvia Regina Lucas de; Lima,Karla Andrea Oliveira de; Carvalho,Thayla Morandi Ridolfi de; Bueno,Leda Gobbo de Freitas.
Production losses due to lack of precision in detecting estrus in dairy cows are well known and reported in milk production countries. Nowadays automatic estrus detection has become possible as a result of technical progress in continuously monitoring dairy cows using fuzzy pertinence functions. Dairy cow estrus is usually visually detected; however, solely use of visual detection is considered inefficient. Many studies have been carried out to develop an effective model to interpret the occurrence of estrus and detect estrus; however, most models present too many false-positive alerts and because of this they are sometimes considered unreliable. The objective of this research was to construct a system based on fuzzy inference functions evaluated with a...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Estrus cycle; Artificial intelligence; Expert system.
Ano: 2010
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162010000500002

Simulation of Agricultural Logistic Processes with k-Nearest Neighbors Algorithm
Provedor de dados: 111
Autores: Bernhardt, Heinz.
The topic logistic has become more and more important in German agriculture during the last years. This is caused by a growth of enterprises and machines but also be the enormous extension of the cultivation of renewable resources for the production of energy.  To manage these logistical tasks in agriculture in Germany at the moment different transport systems are preferred. The classical system with tractor and agricultural trailer, transport via truck like it is typical for the commercial transport of goods and the transport with specialized vehicles which can be classified between both systems. To evaluate these transport processes it is decisive for the farmers to know the key parameters of the single systems like the average fuel consumption (energy)...
Tipo: Info:eu-repo/semantics/article
Ano: 2015
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/3140

Utilization of new computational intelligence methods to estimate daily Evapotranspiration of wheat using Gamma pre processing
Provedor de dados: 111
Autores: mohammadigolafshani, nima; koulaian, ali.
Estimation of evapotranspiration (ET) is needed in water resources management, scheduling of farm irrigation, and environmental assessment. Hence, in practical hydrology, it is often crucial to reliably and constantly estimate evapotranspiration. Accordingly, 3 artificial intelligence (AI) techniques comprising adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and adaptive neuro-fuzzy inference- wavelet (ANFIS-Wavelet) were applied in to estimate wheat crop evapotranspiration (ETc). A case study in a Dashtenaz region located in Mazandaran, Iran, was conducted with weather daily data, including maximum temperature, minimum temperature, maximum relative humidity, minimum relative humidity, wind speed, and solar radiation since...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Adaptive neuro-fuzzy inference system; Adaptive neuro-fuzzy inference-wavelet; Evapotranspiration; Neural network; Wheat.
Ano: 2018
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/4459

Fuzzy Water Irrigation System using Internet of Things
Provedor de dados: 111
Autores: Dhumale, Rakesh Dhumale.
Water is basic source of the farming with limited storage. Out of available land 64% is engaged by the farming and needs nearly 85 % of clean water of total water storage. Proper irrigation helps to improve quality of soil and the growth of crops. The farmer depending upon condition of soil and available water resource has to apply intelligence to get realistic decisions to reduce the wastage of water and ensure full utilization of the water. This gives challenging opportunity to pertain theory and idea of Artificial Intelligence (AI) in the process of water irrigation. In this paper, an intelligent approach for the water irrigation of crop is proposed. Smart Fuzzy Water Irrigation System (FWIS) using Internet of Things (IoT) includes two types of nodes...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Irrigation system; Fuzzy logic; Internet of Things; Soil parameters.
Ano: 2023
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/5398

Phytoplankton Diversity in the Mediterranean Sea From Satellite Data Using Self-Organizing Maps
Provedor de dados: 5
Autores: El Hourany, Roy; Abboud-abi Saab, Marie; Faour, Ghaleb; Mejia, Carlos; Crepon, Michel; Thiria, Sylvie.
We present a new method to identify phytoplankton functional types (PFTs) in the Mediterranean Sea from ocean color data (GlobColour data in the present study) and AVHRR sea surface temperature. The principle of the method is constituted by two very fine clustering algorithms, one mapping the relationship between the satellite data and the pigments and the other between the pigments and the PFTs. The clustering algorithms are constituted of two efficient self-organizing maps, which are neural network classifiers. We were able to identify and estimate the percentage of six PFTs: haptophytes, chlorophytes, cryptophytes, Synechococcus, Prochlorococcus, and diatoms. We found that these PFTs present a peculiar variability due to the complex physical and...
Tipo: Text
Palavras-chave: Phytoplankton; Secondary phytoplankton pigments; Self-organizing maps; Classification; Mediterranean Sea; Remote sensing.
Ano: 2019
URL: https://archimer.ifremer.fr/doc/00589/70145/68135.pdf

Toward a European Coastal Observing Network to Provide Better Answers to Science and to Societal Challenges; The JERICO Research Infrastructure
Provedor de dados: 5
Autores: Farcy, Patrick; Durand, Dominique; Charria, Guillaume; Painting, Suzanne J.; Tamminem, Timo; Collingridge, Kate; Grémare, Antoine J.; Delauney, Laurent; Puillat, Ingrid.
The coastal area is the most productive and dynamic environment of the world ocean, offering significant resources and services for mankind. As exemplified by the UN Sustainable Development Goals, it has a tremendous potential for innovation and growth in blue economy sectors. Due to the inherent complexity of the natural system, the answers to many scientific and societal questions are unknown, and the impacts of the cumulative stresses imposed by anthropogenic pressures (such as pollution) and climate change are difficult to assess and forecast. A major challenge for the scientific community making observations of the coastal marine environment is to integrate observations of Essential Ocean Variables for physical, biogeochemical, and biological...
Tipo: Text
Palavras-chave: European Research Infrastructure; JERICO and JERICO-NEXT; Coastal essential ocean variables; Coastal observatories; High frequency; Physics; Biogeochemistry and biology.
Ano: 2019
URL: https://archimer.ifremer.fr/doc/00514/62595/66955.pdf

A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses
Provedor de dados: 5
Autores: Howell, Kerry L.; Davies, Jaime S.; Allcock, A. Louise; Braga-henriques, Andreia; Buhl-mortensen, Pål; Carreiro-silva, Marina; Dominguez-carrió, Carlos; Durden, Jennifer M.; Foster, Nicola L.; Game, Chloe A.; Hitchin, Becky; Horton, Tammy; Hosking, Brett; Jones, Daniel Ob; Mah, Christopher; Laguionie Marchais, Claire; Menot, Lenaick; Morato, Telmo; Pearman, Tabitha R. R.; Piechaud, Nils; Ross, Rebecca E.; Ruhl, Henry A.; Saeedi, Hanieh; Stefanoudis, Paris V.; Taranto, Gerald H.; Thompson, Michael B.; Taylor, James R.; Tyler, Paul; Vad, Johanne; Victorero, Lissette; Vieira, Rui P.; Woodall, Lucy C.; Xavier, Joana R.; Wagner, Daniel.
Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of artificial intelligence to...
Tipo: Text
Ano: 2019
URL: https://archimer.ifremer.fr/doc/00602/71408/69862.pdf

Nanoscience and Nano-Technology: Cracking Prodigal Farming
Provedor de dados: 17
Autores: Siddhartha S. Mukhopadhyay; Vir Rajinder  Parshad; Inderpreet S. Gill.
Nano-science coupled with nano-technology has emerged as possible cost-cutting measure to prodigal farming and environmental clean-up operations. It has ushered as a new interdisciplinary field by converging various science disciplines, and is highly relevant to agricultural and food systems.  Environmental Protection Agency of USA defined nanotechnology as the understanding and control of matter at dimensions of roughly 1-100 nm, where unique physical properties make novel applications possible. By this definition all soil-clays, many chemicals derived from soil organic matter (SOM), several soil microorganisms fall into this category. Apart from native soil-materials, many new nanotech products are entering into soil system, some of which are used for...
Tipo: Manuscript
Palavras-chave: Chemistry; Ecology; Earth &amp; Environment.
Ano: 2009
URL: http://precedings.nature.com/documents/3203/version/1

Study of stem form using artificial neural networks and taper functions
Provedor de dados: 190
Autores: Schikowski, Ana Beatriz; Dalla Corte, Ana Paula; Sanquetta, Carlos Roberto.
Artificial neural networks (ANN) have great potential as an alternative to conventional regression analysis because of its learning capacity of data set information and the generalization of learning to unknown data. So, the aim of this study was to apply RNAs to estimate relative diameter, total and commercial volume, as well as to compare their performance in relation to conventional taper functions. Data from 47 trees of Eucalyptus sp. were used in the training and validation of ANNs and in adjusting Hradetzky and Garay taper functions. The performance of ANNs were similar to the taper functions for diameter estimative, furthermore the estimative of commercial and total volume applying ANNs were more accurate and presented less residues scattering than...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Cubage; Eucalypt; Artificial intelligence Engenharia Florestal; Manejo Florestal Cubagem; Eucalipto; Inteligência artificial.
Ano: 2015
URL: http://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/867

Modeling Advertising Expenditures and Spillover Effects Applied to the U.S. Non-Alcoholic Beverage Industry: Vector Autoregression (VAR) and Polynomial Distributed Lag (PDL) Approaches
Provedor de dados: 31
Autores: Dharmasena,   Senarath; Capps,   Oral, Jr.; Bessler,   David A.
The non-alcoholic beverage market in the U.S. is a multi-billion dollar industry growing steadily over the past decade. Also, non-alcoholic beverages are among the most heavily advertised food and beverage groups in the United States. Several studies pertaining to non-alcoholic beverages including the incorporation of advertising effects have been conducted, but most of these have centered attention on milk consumption. Some studies have considered demand interrelationships for several beverages including advertising effects in systems-wide analyses.  In our analysis, we develop and employ a unique monthly time-series data set derived from Nielsen Homsescan panels for household purchases of non-alcoholic beverages over the period from January 1998 through...
Tipo: Presentation
Palavras-chave: Non-alcoholic beverages; Vector autoregression; Polynomial distributed lags; Beverage advertizing; Directed acyclic graphs; Agricultural and Food Policy; Consumer/Household Economics; Demand and Price Analysis; Food Consumption/Nutrition/Food Safety; Marketing; C18; C22; C52; C53; C81; D11; D12.
Ano: 2012
URL: http://purl.umn.edu/124363

SUPPORT VECTOR MACHINE TO ESTIMATE THE SOYBEAN YIELD
Provedor de dados: 107
Autores: Michelon, Gabriela Karoline; de Menezes, Paulo Lopes; Júnior, Arnaldo Cândido; Bazzi, Claudio Leones; Barbosa, Marcela Marques.
Soybean is one of the major oleaginous, used for food and feed to processed products and also as an alternative source of biofuel. Due to its great uses that is highly valued and cultivated in the world. Therefore, this study sought to apply an artificial intelligence technique to predict soybean yield and therefore maximize production from farmlands, increase the profit of the producer and reduce environmental impacts. There were then used the support vector machine technique, to find a prediction model of soybean yield from the leaf nutrients, allowing therefore that fertilization is carried out only in necessary locations predicted as low productivity points for best support vector machine model obtained. Among all created models, the best prediction of...
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Agricultura de Precisão Inteligência Artificial; Nutrientes Foliares; Regressão.
Ano: 2017
URL: http://www.seer.ufv.br/seer/index.php/reveng/article/view/745

Use of artificial intelligence (artificial neural networks) to classify the pathogenicity of Escherichia coli isolates from broilers
Provedor de dados: 195
Autores: Salle, C. T. P.; Rocha, A. C. G. P.; Souza, G. F.; Salle, F. O.; Moraes, L. B.; Nascimento, V. P.; Moraes, H. L. S.
This article has no abstract.
Tipo: Info:eu-repo/semantics/article
Ano: 2011
URL: http://www.revistamvez-crmvsp.com.br/index.php/recmvz/article/view/54

Evaluación de métodos para la cartografía digital de clases de  tierra campesinas
Provedor de dados: 32
Autores: Cruz Cárdenas, Gustavo.
El mapeo digital de suelos consiste en emplear algoritmos computacionales y predictores que  representan las variables para la generación de mapas de suelos. Existen evidencias que estos  mapas son confiables. Sin embargo, para la elaboración de mapas de clases de tierra  campesinas, utilizando técnicas digitales se tiene poca información y los mapas producidos  son de baja calidad porque han utilizado sólo los valores de reflectancias de las clases de  tierras como predictores y algoritmos limitados en cuanto a su configuración. Por lo anterior,  en esta investigación se evaluó la calidad de los mapas de clases de tierra campesinas  generados en México, en condiciones ambientales contrastantes (árida, templada y tropical), a  partir de técnicas empleadas...
Tipo: Tesis
Palavras-chave: Precisión y exactitud de mapas; Imágenes de satélite; Atributos topográficos; Inteligencia artificial; Tamaño y diseño de muestro espacial; Doctorado; Edafología; Precision and accuracy of maps; Remote sensing data; Topographic attributes; Artificial intelligence; Size and spatial sampling design.
Ano: 2009
URL: http://hdl.handle.net/10521/1483

Altimetry for the future: Building on 25 years of progress
Provedor de dados: 5
Autores: Abdalla, Saleh; Abdeh Kolahchi, Abdolnabi; Adusumilli, Susheel; Aich Bhowmick, Suchandra; Alou-font, Eva; Amarouche, Laiba; Andersen, Ole Baltazar; Antich, Helena; Aouf, Lotfi; Arbic, Brian; Armitage, Thomas; Arnault, Sabine; Artana, Camila; Aulicino, Giuseppe; Ayoub, Nadia; Badulin, Sergei; Baker, Steven; Banks, Chris; Bao, Lifeng; Barbetta, Silvia; Barceló-llull, Bàrbara; Barlier, François; Basu, Sujit; Bauer-gottwein, Peter; Becker, Matthias; Beckley, Brian; Bellefond, Nicole; Belonenko, Tatyana; Benkiran, Mounir; Benkouider, Touati; Bennartz, Ralf; Benveniste, Jérôme; Bercher, Nicolas; Berge-nguyen, Muriel; Bettencourt, Joao; Blarel, Fabien; Blazquez, Alejandro; Blumstein, Denis; Bonnefond, Pascal; Borde, Franck; Bouffard, Jérôme; Boy, François; Boy, Jean-paul; Brachet, Cédric; Brasseur, Pierre; Braun, Alexander; Brocca, Luca; Brockley, David; Brodeau, Laurent; Brown, Shannon; Bruinsma, Sean; Bulczak, Anna; Buzzard, Sammie; Cahill, Madeleine; Calmant, Stéphane; Calzas, Michel; Camici, Stefania; Cancet, Mathilde; Capdeville, Hugues; Carabajal, Claudia Cristina; Carrere, Loren; Cazenave, Anny; Chassignet, Eric P.; Chauhan, Prakash; Cherchali, Selma; Chereskin, Teresa; Cheymol, Cecile; Ciani, Daniele; Cipollini, Paolo; Cirillo, Francesca; Cosme, Emmanuel; Coss, Steve; Cotroneo, Yuri; Cotton, David; Couhert, Alexandre; Coutin-faye, Sophie; Crétaux, Jean-françois; Cyr, Frederic; D’ovidio, Francesco; Darrozes, José; David, Cedric; Dayoub, Nadim; De Staerke, Danielle; Deng, Xiaoli; Desai, Shailen; Desjonqueres, Jean-damien; Dettmering, Denise; Di Bella, Alessandro; Díaz-barroso, Lara; Dibarboure, Gerald; Dieng, Habib Boubacar; Dinardo, Salvatore; Dobslaw, Henryk; Dodet, Guillaume; Doglioli, Andrea; Domeneghetti, Alessio; Donahue, David; Dong, Shenfu; Donlon, Craig; Dorandeu, Joël; Drezen, Christine; Drinkwater, Mark; Du Penhoat, Yves; Dushaw, Brian; Egido, Alejandro; Erofeeva, Svetlana; Escudier, Philippe; Esselborn, Saskia; Exertier, Pierre; Fablet, Ronan; Falco, Cédric; Farrell, Sinead Louise; Faugere, Yannice; Femenias, Pierre; Fenoglio, Luciana; Fernandes, Joana; Fernández, Juan Gabriel; Ferrage, Pascale; Ferrari, Ramiro; Fichen, Lionel; Filippucci, Paolo; Flampouris, Stylianos; Fleury, Sara; Fornari, Marco; Forsberg, Rene; Frappart, Frédéric; Frery, Marie-laure; Garcia, Pablo; Garcia-mondejar, Albert; Gaudelli, Julia; Gaultier, Lucile; Getirana, Augusto; Gibert, Ferran; Gil, Artur; Gilbert, Lin; Gille, Sarah; Giulicchi, Luisella; Gómez-enri, Jesús; Gómez-navarro, Laura; Gommenginger, Christine; Gourdeau, Lionel; Griffin, David; Groh, Andreas; Guerin, Alexandre; Guerrero, Raul; Guinle, Thierry; Gupta, Praveen; Gutknecht, Benjamin D.; Hamon, Mathieu; Han, Guoqi; Hauser, Danièle; Helm, Veit; Hendricks, Stefan; Hernandez, Fabrice; Hogg, Anna; Horwath, Martin; Idžanović, Martina; Janssen, Peter; Jeansou, Eric; Jia, Yongjun; Jia, Yuanyuan; Jiang, Liguang; Johannessen, Johnny A.; Kamachi, Masafumi; Karimova, Svetlana; Kelly, Kathryn; Kim, Sung Yong; King, Robert; Kittel, Cecile M.m.; Klein, Patrice; Klos, Anna; Knudsen, Per; Koenig, Rolf; Kostianoy, Andrey; Kouraev, Alexei; Kumar, Raj; Labroue, Sylvie; Lago, Loreley Selene; Lambin, Juliette; Lasson, Léa; Laurain, Olivier; Laxenaire, Rémi; Lázaro, Clara; Le Gac, Sophie; Le Sommer, Julien; Le Traon, Pierre-yves; Lebedev, Sergey; Léger, Fabien; Legresy, Benoı̂t; Lemoine, Frank; Lenain, Luc; Leuliette, Eric; Levy, Marina; Lillibridge, John; Liu, Jianqiang; Llovel, William; Lyard, Florent; Macintosh, Claire; Makhoul Varona, Eduard; Manfredi, Cécile; Marin, Frédéric; Mason, Evan; Massari, Christian; Mavrocordatos, Constantin; Maximenko, Nikolai; Mcmillan, Malcolm; Medina, Thierry; Melet, Angelique; Meloni, Marco; Mertikas, Stelios; Metref, Sammy; Meyssignac, Benoit; Michaël, Ablain; Minster, Jean-françois; Moreau, Thomas; Moreira, Daniel; Morel, Yves; Morrow, Rosemary; Moyard, John; Mulet, Sandrine; Naeije, Marc; Nerem, Robert Steven; Ngodock, Hans; Nielsen, Karina; Nilsen, Jan Even Øie; Niño, Fernando; Nogueira Loddo, Carolina; Noûs, Camille; Obligis, Estelle; Otosaka, Inès; Otten, Michiel; Oztunali Ozbahceci, Berguzar; P. Raj, Roshin; Paiva, Rodrigo; Paniagua, Guillermina; Paolo, Fernando; Paris, Adrien; Pascual, Ananda; Passaro, Marcello; Paul, Stephan; Pavelsky, Tamlin; Pearson, Christopher; Penduff, Thierry; Peng, Fukai; Perosanz, Felix; Picot, Nicolas; Piras, Fanny; Poggiali, Valerio; Poirier, Étienne; Ponce De León, Sonia; Prants, Sergey; Prigent, Catherine; Provost, Christine; Pujol, M-isabelle; Qiu, Bo; Quilfen, Yves; Rami, Ali; Raney, R. Keith; Raynal, Matthias; Remy, Elisabeth; Rémy, Frédérique; Restano, Marco; Richardson, Annie; Richardson, Donald; Ricker, Robert; Ricko, Martina; Rinne, Eero; Rose, Stine Kildegaard; Rosmorduc, Vinca; Rudenko, Sergei; Ruiz, Simón; Ryan, Barbara J.; Salaün, Corinne; Sanchez-roman, Antonio; Sandberg Sørensen, Louise; Sandwell, David; Saraceno, Martin; Scagliola, Michele; Schaeffer, Philippe; Scharffenberg, Martin G.; Scharroo, Remko; Schiller, Andreas; Schneider, Raphael; Schwatke, Christian; Scozzari, Andrea; Ser-giacomi, Enrico; Seyler, Frederique; Shah, Rashmi; Sharma, Rashmi; Shaw, Andrew; Shepherd, Andrew; Shriver, Jay; Shum, C.k.; Simons, Wim; Simonsen, Sebatian B.; Slater, Thomas; Smith, Walter; Soares, Saulo; Sokolovskiy, Mikhail; Soudarin, Laurent; Spatar, Ciprian; Speich, Sabrina; Srinivasan, Margaret; Srokosz, Meric; Stanev, Emil; Staneva, Joanna; Steunou, Nathalie; Stroeve, Julienne; Su, Bob; Sulistioadi, Yohanes Budi; Swain, Debadatta; Sylvestre-baron, Annick; Taburet, Nicolas; Tailleux, Rémi; Takayama, Katsumi; Tapley, Byron; Tarpanelli, Angelica; Tavernier, Gilles; Testut, Laurent; Thakur, Praveen K.; Thibaut, Pierre; Thompson, Luanne; Tintoré, Joaquín; Tison, Céline; Tourain, Cédric; Tournadre, Jean; Townsend, Bill; Tran, Ngan; Trilles, Sébastien; Tsamados, Michel; Tseng, Kuo-hsin; Ubelmann, Clément; Uebbing, Bernd; Vergara, Oscar; Verron, Jacques; Vieira, Telmo; Vignudelli, Stefano; Vinogradova Shiffer, Nadya; Visser, Pieter; Vivier, Frederic; Volkov, Denis; Von Schuckmann, Karina; Vuglinskii, Valerii; Vuilleumier, Pierrik; Walter, Blake; Wang, Jida; Wang, Chao; Watson, Christopher; Wilkin, John; Willis, Josh; Wilson, Hilary; Woodworth, Philip; Yang, Kehan; Yao, Fangfang; Zaharia, Raymond; Zakharova, Elena; Zaron, Edward D.; Zhang, Yongsheng; Zhao, Zhongxiang; Zinchenko, Vadim; Zlotnicki, Victor.
In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and...
Tipo: Text
Palavras-chave: Satellite altimetry; Oceanography; Sea level; Coastal oceanography; Cryospheric sciences; Hydrology.
Ano: 2021
URL: https://archimer.ifremer.fr/doc/00688/79999/82978.pdf