Deep Learning Based Prediction of Cotton Crop Production in India
In this paper, forecasting of production of Cotton (Million Tones) using Auto Regressive Integrated Moving Averages (ARIMA) method, Recurrent Neural Network (RNN), Multilayer Perceptron (MLP), Convolution Neural Networks (CNN) and Long Short- term memory (LSTM) are presented. The appropriate best model is evaluated by comparing mean square error (MSE), Root mean square error (RMSE), mean absolute percentage error (MAPE). The study of the results shows that LSTM is performing better than the other models ARIMA, RNN, MLP and CNN. The forecasted production of Cotton shows downward tendency from 2019-20 to 2028-29.