Abstract
Both Genetic Algorithms (GA) and Artificial Neural Networks (ANN) are extensively employed for predictive analysis in the research study. Agriculture is the foundation of our country and Rice production is one of the major crops in India. Thus, predictive modelling of rice production becomes extremely important task. This paper aims to develop a Hybrid model using ANN with GA to carry out predictive modelling of rice in order to generate superior prediction. The proposed model is tested on Rice production in India from 1981 to 2003. The prediction performance is evaluated using error calculation techniques indices like ‘Mean Squared Error’ (MSE), ‘Root Mean Square Error’ (RMSE) and ‘Mean Absolute Percentage Error’ (MAPE). Which is recognized that the error of prediction is minimized using our proposed hybrid model in comparison to the existing model where Artificial Neural Network is used exclusively.
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