Intelligent Modeling of Sugar-Cane Maturation
Salomão Sampaio Madeiro, Flávio Rosendo da Silva Oliveira, Frederico Bruno Alves Alexandre, Fernando Buarque de Lima Neto · Computers in Agriculture and Natural Resources, 23-25 July 2006, Orlando Florida · 2013
Previous use of Artificial Intelligence (AI) in agriculture for forecasting productivityindicators, especially Artificial Neural Networks (ANN), has shown that it is possible to approximatesugarcane maturation curves. However, ANNs are widely known to offer some difficulties to beparameterized; normally, some heuristics and devotion by the users are necessary to provide a suitableparametrical selection. In this work we propose a tool that searches ANN parameters automatically (i.e.without direct interference of users in this task). For this high goal, we utilized another artificial intelligenttechnique: Genetic Algorithms (GA). The paper concludes showing results of ANNs which parameters havebeen provided by (the contributed) automated approach; comparisons to manually setup ANNs are included.