Modeling Method Based on Smooth Support Vector Regression with Independent Component Analysis Feature Extraction

Xu Sheng Gan; Xue Qin Tang; Hai Long Gao

doi:10.4028/www.scientific.net/AMM.713-715.1773

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 713-715Modeling Method Based on Smooth Support Vector...

Modeling Method Based on Smooth Support Vector Regression with Independent Component Analysis Feature Extraction

Abstract:

Smooth Support Vector Regression (SSVR) is new modified edition of traditional support vector regression for better performance. To further improve the modeling capability of SSVR, it is necessary to take into account the feature extraction based on Independent Component Analysis (ICA) before SSVR. Simulation on the example of function approximation shows that the result of SSVR based on ICA feature extraction is better than that of SSVR without ICA preprocess.

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Periodical:

Applied Mechanics and Materials (Volumes 713-715)

Pages:

1773-1776

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.713-715.1773

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Online since:

January 2015

Authors:

Xu Sheng Gan*, Xue Qin Tang, Hai Long Gao

Keywords:

Feature Extraction, Independent Component Analysis, Quadratic Optimization, Smooth Support Vector Regression

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* - Corresponding Author

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