The accurate estimation of rice production is very essential to make better planning and decision making for any Government. In this paper, we forecast rice production by using time series model like Auto Regressive Integrated Moving Average (ARIMA). Also, we forecast rice production by using Artificial Neural Networks (ANN) multilayer perceptron model. Further, we find mean absolute error (MAE) and Root Mean Squared Error (RMSE) of the time series model and ANN model. To study the models, we used time series record of rice production in India from 1960 to 2018. Results show that ANN model appears to perform better than conventional time series models in forecasting.
ARIMA, Artificial Neural Networks, MAE and RMSE, Forecasting
