The Study on Corn Production Prediction in Heilongjiang Province Based on Support Vector Machine

This paper uses the support vector machine (SVM) algorithm to study the prediction of corn production in Heilongjiang province, forms the sample set with the 1991-2008 data in Heilongjiang province, and set up the SVM model between factors and corn production. Use SVM on the input and output data for training and learning, approximate the implied function relationship by historical data, complete the mapping of the new data series, in order to complete the corn production prediction for future years, and compare the prediction effects with other methods. The results show that, the prediction accuracy of corn production of the SVM model is superior to other prediction methods.