Sports Economic Activities Income Forecasting based on Genetic Support Vector Regression Algorithm

Abstract

In order to solve the shortcoming of support vector regression algorithm, sports economic activities income forecasting based on genetic support vector regression algorithm is presented in this paper. As the kernel parameter, insensitive loss parameter and penalty parameter have a great influence on the forecasting performance of support vector regression algorithm, genetic algorithm is used to perform the parameters optimization of support vector regression algorithm simultaneously in this study. The experimental results show that the sports economic activities income forecasting results of genetic support vector regression model trained by the four-dimension training samples are more excellent than those of genetic support vector regression model trained by the three-dimension training samples, and the sports economic activities income forecasting ability of genetic support vector regression model trained by the four- dimension training samples is better than that of support vector regression model trained by the four-dimension training samples. Thus, genetic support vector regression algorithm has a good application prospect in sports economic activities income forecasting.