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| Registros recuperados: 64 | |
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| 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 |
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| 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.

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 |
| Tipo: Presentation |
Palavras-chave: Ecology; Bioinformatics. |
| Ano: 2008 |
URL: http://precedings.nature.com/documents/2003/version/1 |
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| 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... |
| 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 |
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| 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... |
| 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 |
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| 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: ‘Deliberative-decisive’ 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 |
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| 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... |
| Tipo: Working or Discussion Paper |
Palavras-chave: Environmental Economics and Policy. |
| Ano: 2002 |
URL: http://purl.umn.edu/11549 |
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| 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 |
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| 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 |
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| 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... |
| 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 |
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| 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... |
| 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 |
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| 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 |
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| Ano: 2015 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/3140 |
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| 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... |
| 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 |
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| 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 |
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| Campos, Bráulio Pizziôlo Furtado; Silva, Gilson Fernandes da; Binoti, Daniel Henrique Breda; Mendonça, Adriano Ribeiro de; Leite, Helio Garcia. |
| The objective of this study was to analyze the ability of an artificial neural network (ANN) to describe the stem profile of trees of different genera and species in different growing conditions. For comparative purposes, equations were fit, using regression analysis to describe the stem profile. For neural network as well as for the regression equations, evaluation of accuracy was based on correlation coefficient between observed and estimated diameters along the stem, square root of the mean square percentage error (RMSE) and graphical analysis. Artificial intelligence methods, especially ANN, can be effective in describing trees bole profile of different species in different growth... |
| 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 |
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| 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 |
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| Registros recuperados: 64 | |
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