Author:
Lorençone João Antonio,Lorençone Pedro Antonio,Aparecido Lucas Eduardo Oliveira,Torsoni Guilherme Botega,Ferreira Lucas da Rocha
Abstract
This study aimed to perform the agricultural zoning of climatic risk for bamboo in Brazil by means of artificial neural networks. It was used climatic data of air temperature (TAIR, ºC) and rainfall (P). The Feed Forward Artificial Neural Network, Multilayer Perceptron (MLP) with backpropagation learning algorithm for multilayers was employed. The agroclimatic zoning allowed the classification of regions by climatic suitability and showed that 71% of the national territory was suitable for bamboo cultivation. The use of the neural network allowed an accurate and fast classification of climate suitability.
Publisher
South Florida Publishing LLC
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