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10.1109/ISCID.2013.49guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
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Particle Swarm Optimization-Least Squares Support Vector Regression with Multi-scale Wavelet Kernel

Published: 28 October 2013 Publication History

Abstract

A novel regression model combining least squares support vector regression (LS-SVR) with multi-scale wavelet kernel and particle swarm optimization (PSO) was presented in this paper, and applied to the approximation of non-stationary dataset and those continuous functions polluted by strong noise. Support vector kernel function with the multi-resolution characteristics was employed, such that LS-SVR with multi-scale wavelet kernel can estimate each details of target function accurately. The experimental results show that the proposed method is effective and feasible.

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Published In

cover image Guide Proceedings
ISCID '13: Proceedings of the 2013 Sixth International Symposium on Computational Intelligence and Design - Volume 01
October 2013
443 pages
ISBN:9780769550794

Publisher

IEEE Computer Society

United States

Publication History

Published: 28 October 2013

Author Tags

  1. least squares support vector regression
  2. multi-scale
  3. particle swarm optimization
  4. strong noise
  5. wavelet kernel

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