Prediction of Chongqing's grain output based on support vector machine

Abstract

Scientific prediction of agricultural food production plays an essential role in stabilizing food supply. In order to improve the accuracy of grain yield prediction and reduce the error of grain yield prediction in Chongqing, this paper proposes a new method for the grain yield prediction in Chongqing by using support vector machine (SVM). In this paper, based on the support vector regression structure, the support vector regression algorithm is designed, and then the support vector machine is adopted in the replacement of the error back propagation process in BP neural network. The results of case analysis show that the method based on support vector machine can effectively reduce the error of grain yield prediction.