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Description of epidemics of coffee rust with neural networks Trop. Plant Pathol.
PINTO,AUGUSTO CARLOS S.; POZZA,EDSON A.; SOUZA,PAULO E. DE; POZZA,ADÉLIA A. A.; TALAMINI,VIVIANE; BOLDINI,JULIANA M.; SANTOS,FLORISVALDA S..
The objective of this paper was to evaluate the potential of neural networks (NN) as an alternative method to the basic epidemiological approach to describe epidemics of coffee rust. The NN was developed from the intensities of coffee (Coffea arabica) rust along with the climatic variables collected in Lavras-MG between 13 February 1998 and 20 April 2001. The NN was built with climatic variables that were either selected in a stepwise regression analysis or by the Braincel® system, software for NN building. Fifty-nine networks and 26 regression models were tested. The best models were selected based on small values of the mean square deviation (MSD) and of the mean prediction error (MPE). For the regression models, the highest coefficients of determination...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Inteligência artificial; Epidemiologia; Hemileia vastatrix; Coffea arabica.
Ano: 2002 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-41582002000500013
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