Role of Statistical Soft Computing in Agricultural Price Forecasting

Abstract

Statistical Soft computing & Time series modelling is a dynamic research, which aims to carefully collect and rigorously study the past observations of a time series to develop an appropriate model which describes the inherent structure of the series. Time series forecasting thus can be termed as the act of predicting the future by understanding the past. Price forecasting help famers to take effective decision regarding market price (mandi price) or selling price of their crop, which crop to grow to earn profit, ultimately improve the condition and income of famer and also helps policy maker for agriculture decision. For price forecasting of agricultural crops ARIMA (Auto Regressive Integrated Moving Average) Model & ANN (Artificial Neural Network) is used. Neural Network approaches are applied in the field of agriculture for price forecasting in both short term and long terms Forecasting.