Transcription of ARTIFICIAL NEURAL NETWORKS - IASRI
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ARTIFICIAL NEURAL NETWORKS - IASRI
ARTIFICIAL NEURAL NETWORKS GIRISH KUMAR JHA Indian Agricultural Research Institute PUSA, New Delhi-110 012 1. Introduction ARTIFICIAL NEURAL NETWORKS (ANNs) are non-linear mapping structures based on the function of the human brain. They are powerful tools for modelling, especially when the underlying data relationship is unknown. ANNs can identify and learn correlated patterns between input data sets and corresponding target values. After training, ANNs can be used to predict the outcome of new independent input data. ANNs imitate the learning process of the human brain and can process problems involving non-linear and complex data even if the data are imprecise and noisy. Thus they are ideally suited for the modeling of agricultural data which are known to be complex and often non-linear.
A Artificial Neural Networks 3 crop evapotranspiration and compared the performance of ANNs with the conventional method used to estimate evapotranspiration.
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