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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lin Shi-Ting Xue Bo |
| Copyright Year | 2014 |
| Description | Author affiliation: Qinhuangdao Inst. of Technol., Qinhuangdao, China (Lin Shi-Ting; Xue Bo) |
| Abstract | 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. |
| Sponsorship | Shenzhen Res. Inst., Central South Univ. |
| Starting Page | 769 |
| Ending Page | 772 |
| File Size | 310546 |
| Page Count | 4 |
| File Format | |
| e-ISBN | 9781479966363 |
| DOI | 10.1109/ICICTA.2014.186 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-10-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines Correlation coefficient Tourism Economy Time series analysis Predictive models Data Analysis Prediction algorithms Data models Support Vector Machine Kernel |
| Content Type | Text |
| Resource Type | Article |
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