The Application of Improved SVM for Data Analysis in Tourism Economy

In this thesis, the main content of statistical learning theory is firstly introduced briefly, based on this, the basic principle and process of ε-SVR (one algorithm of Support Vector Machine for Regression, SVR) is presented. Then this method is used to model tourist traffic prediction and predict one series data (Taian monthly tourist quantity data). Two different kernel functions are employed, and the former´s performance is evidently better than the latter´s. ε-SVR´s performance is also compared with that of traditional time series analysis method, and the former outperforms the latter.