Hyper-Parameters Selection of LS-SVM Based on PSO Algorithm with Multi-Particles Sharing Strategy

Jie Liu; Xu Sheng Gan; Wen Ming Gao

doi:10.4028/www.scientific.net/AMR.1049-1050.1654

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 1049-1050Hyper-Parameters Selection of LS-SVM Based on PSO...

Hyper-Parameters Selection of LS-SVM Based on PSO Algorithm with Multi-Particles Sharing Strategy

Abstract:

To optimize the parameters of LS-SVM effectively, an improved Particle Swarm Optimization (PSO) algorithm is proposed to select the optimal parameters combination. For the improvement of the precocity in PSO algorithm, an multi-particles sharing strategy is introduced in simple PSO algorithm to enhance the convergence. The simulation indicates that the proposed PSO algorithm has a better selection on LS-SVM parameters.

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Periodical:

Advanced Materials Research (Volumes 1049-1050)

Pages:

1654-1657

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1049-1050.1654

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Online since:

October 2014

Authors:

Jie Liu*, Xu Sheng Gan, Wen Ming Gao

Keywords:

Hyper-Parameters Selection, Least Square, Multi-Particles Sharing Strategy, Particle Swarm Optimization (PSO), Support Vector Machine (SVM)

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* - Corresponding Author

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