A Parameter Choosing Method of SVR for Time Series Prediction

被引：0

作者：

Lin, Shukuan ^{[1
]}

Zhang, Shaomin ^{[1
]}

Qiao, Jianzhong ^{[1
]}

Liu, Hualei ^{[1
]}

Yu, Ge ^{[1
]}

机构：

[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110004, Liaoning, Peoples R China

来源：

PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE FOR YOUNG COMPUTER SCIENTISTS, VOLS 1-5 | 2008年

关键词：

Parameter choosing; SVR; time series prediction; improved Cross-Validation; epsilon-weighed;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

It is important to choose good parameters in Support Vector Regression (SVR) modeling. Choosing different parameters will influence the accuracy of SVR models. This paper proposes a parameter choosing method of SVR models for time series prediction. In the light of data features of time series, the paper improves the traditional Cross-Validation method, and combines the improved Cross-Validation with epsilon-weighed SVR in order to get good parameters of models. The experiments show that the method is effective for time series prediction.

引用

页码：130 / 135

页数：6

共 50 条

[1] A HYBRID METHOD FOR TIME SERIES PREDICTION USING EMD AND SVR
Bican, Bahadir
Yaslan, Yusuf
2014 6TH INTERNATIONAL SYMPOSIUM ON COMMUNICATIONS, CONTROL AND SIGNAL PROCESSING (ISCCSP), 2014, : 566 - 569
[2] Ensemble SVR for prediction of time series
Deng, YF
Jin, X
Zhong, YX
PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9, 2005, : 3528 - 3534
[3] LS-SVR and AGO Based Time Series Prediction Method
ZHANG Shou-peng
LIU Shan
CHAI Wang-xu
ZHANG Jia-qi
GUO Yang-ming
International Journal of Plant Engineering and Management, 2016, 21 (01) : 1 - 13
[4] Time Series Weighted Prediction Method Using Multikernel LS-SVR
Zhou, Guo-Chang
Guo, Yang-Ming
Ma, Jie-Zhong
PROCEEDINGS OF THE FIRST SYMPOSIUM ON AVIATION MAINTENANCE AND MANAGEMENT, VOL I, 2014, 296 : 251 - 260
[5] Multi-parameter Adaptive Prediction of Chaotic Time series based on LS-SVR
Guo, Yangming
Zhi, Qiang
Wang, Xing
Ma, Jiezhong
Zhu, Peican
2017 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-HARBIN), 2017, : 1207 - 1211
[6] An EMD-SVR Method for Non-Stationary Time Series Prediction
Fan, Jun
Tang, Yanzhen
PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON QUALITY, RELIABILITY, RISK, MAINTENANCE, AND SAFETY ENGINEERING (QR2MSE), VOLS I-IV, 2013, : 1765 - 1770
[7] A method for parameter optimization about the ε-SVR delay prediction
Liu Peiyan
2021 INTERNATIONAL CONFERENCE ON IMAGE, VIDEO PROCESSING, AND ARTIFICIAL INTELLIGENCE, 2021, 12076
[8] Time series prediction based on linear regression and SVR
Lin, Kunhui
Lin, Qiang
Zhou, Changle
Yao, Junfeng
ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 1, PROCEEDINGS, 2007, : 688 - +
[9] ARFNNs with SVR for prediction of chaotic time series with outliers
Fu, Yu-Yi
Wu, Chia-Ju
Jeng, Jin-Tsong
Ko, Chia-Nan
EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (06) : 4441 - 4451
[10] Ensembles Of LS-SVR For Time Series Prediction
Li, Kunlun
Ma, Yinghui
Tian, Yongmei
INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, 2012, 15 (11A): : 4423 - 4428

← 1 2 3 4 5 →