Improved multi-kernel LS-SVR for time series online prediction with incremental learning

Yangming Guo, Xiangtao Wang, Yafei Zheng, Chong Liu

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

Since it is difficult to establish precise physical model of complex systems, time series prediction is often used to predict their health trend and running state. Aiming at online prediction, we proposed a new scheme to fix the problems of time series online prediction, which is based on LS-SVR model and incremental learning algorithm. The scheme includes two aspects. Firstly, by replacing single kernel with new fixed kernel consisting of several basis kernels, a better information mapping in high dimension is obtained; secondly, by establishing new LS-SVR model without bias term b, the calculation process with incremental learning is simplified. Prediction experiment is performed via certain avionics application. The results indicate preliminarily that the proposed scheme is an effective prediction approach for its good prediction precision and less computing time. The method will be useful in actual application.

源语言英语
主期刊名2014 International Conference on Prognostics and Health Management, PHM 2014
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9781479959426
DOI
出版状态已出版 - 9 2月 2015
活动2014 International Conference on Prognostics and Health Management, PHM 2014 - Cheney, 美国
期限: 22 6月 201425 6月 2014

出版系列

姓名2014 International Conference on Prognostics and Health Management, PHM 2014

会议

会议2014 International Conference on Prognostics and Health Management, PHM 2014
国家/地区美国
Cheney
时期22/06/1425/06/14

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