Abstract

In order to improve the predicting correctness of the grain price effectively and offer the theoretical basis for establishing measurement of controlling grain price, the combined prediction algorithm combining the grey prediction model and least squares support vector machine prediction model is applied in predicting the grain price. Firstly, grey prediction model is constructed. Secondly, the least squares support vector machine prediction model is constructed. Thirdly, the combined prediction model is established. Finally, the prediction analysis of grain price is carried out based on combined prediction model and results show that the combined prediction algorithm can improve the prediction precision of grain price effectively.

Keywords:

Grain price, grey prediction model, least squares support vector machine prediction model, prediction and controlling,

References