CROP YIELDING PREDICTION APPLYING REGRESSION: FORECASTING WHEAT/RICE YIELD FOR ANAND DISTRICT
Keywords:
Multiple Linear Regression, Statistics Approaches, Data Mining,Rabi wheat , weather indices,Coefficient of Determination.Abstract
Agrarian territory in India is facing drastic problem to maximize the crop productivity. The problem of yield
prediction is a primary issue that remains to be solved based on receivable statistics. A new later evolution in
Information Technology for agriculture zone has become a charming research area to estimate the crop turn-out. Varied
data Mining techniques are utilized and appraised in agriculture for predicting the forthcoming year’s crop
manufacture. Data mining techniques are the better preference for this objective. The environmental parameters like
rainfall, sunlight, evaporation, Humidity, Temperature etc. that impacts the yield of crop and to implant relationship
among these parameters. Yield prediction boots the peasants in impairing the losses and to get best prices for the crops.
Estimation of food grain production credible omnibus and timely info on the food situation may patronize to the
government policies. This paper represents a concise analysis of crop yield prediction using Multiple Linear Regression
(MLR) technique for the selected domain. By applying Regression and finding the correlation of each parameter with
Yield we are getting our Regression Model that gives 0.95(95%) value of R Square (Coefficient of Determination).
