Abstract
Activation function (AF) plays a vital role in the neural network. This research study focuses on the performance evaluation of the various AFs in multilayer perceptron (MLP) algorithm for the wheat crop yield prediction at the regional level. Nowadays researchers are publishing the new AFs and also proposing the improvement in existing AFs for more accurate results. Sigmoid AF is the default function used in the MLP algorithm. In this research we have applied the various AFs in MLP using the WEKA java libraries and performance analysis has been carried out for the selected districts of the Gujarat state. Based on the mean absolute percentage error (MAPE) performance measure output is discussed. Therefore scientists and researchers can select the appropriate AF to improve the prediction accuracy and hence improve the performance of the network as per the research data.
Neural Network, Activation Function (AF), MLP, Yield Prediction
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