Regression and Neural Networks Models for Prediction of Crop Production

Neural networks have been gaining a great deal of importance and are used in the areas of prediction and classification; the areas where regression and other statistical models are traditionally being used. In this paper, a comprehensive review of literature comparing feedforward neural networks and traditional statistical methods viz. linear regression with respect to prediction of agricultural crop production has been carried out. This study presents a useful insight into the capabilities of neural networks and their statistical counterparts used in the area of prediction of crop yield.