Consulta: subjectFacets:"Artificial intelligence"
Registros recuperados: 23
Data/hora: 02/06/2024 16:56:49

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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