Parameters Optimizing of LSSVM Based on Black Hole Algorithm

doi:10.12068/j.issn.1005-3026.2014.02.005

Journal of Northeastern University Natural Science ›› 2014, Vol. 35 ›› Issue (2): 170-174.DOI: 10.12068/j.issn.1005-3026.2014.02.005

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Parameters Optimizing of LSSVM Based on Black Hole Algorithm

WANG Tong¹， GAO Xianwen¹， JIANG Zijian²

1. School of Information Science & Engineering， Northeastern University， Shenyang 110819， China； 2. School of Electrical Engineering， Shenyang University of Technology， Shenyang 110870， China.

Received:2013-05-27 Revised:2013-05-27 Online:2014-02-15 Published:2013-11-22
Contact: WANG Tong
About author:-
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Abstract

Abstract: Black hole(BH) algorithm is used to search the optimal parameters of least squares support vector machine(LSSVM). Black hole phenomenon in the nature is simulated in BH algorithm， which has the ability to attract the stars moving to it and absorb them in a certain range. During BH algorithm running the entire space is searched through the moving stars and the black hole is considered the optimal solution.In the simulation experiment the twodimensional function is predicted by BHLSSVM and PSOLSSVM respectively. The simulation results show that BH algorithm has excellent capability to search optimal parameters of LSSVM， and BHLSSVM has better capability and higher predictive accuracy.

Key words: black hole algorithm, least squares support vector machine, parameter selection, particle swarm optimization, twodimensional function

CLC Number:

TP29

WANG Tong， GAO Xianwen， JIANG Zijian. Parameters Optimizing of LSSVM Based on Black Hole Algorithm[J]. Journal of Northeastern University Natural Science, 2014, 35(2): 170-174.

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Parameters Optimizing of LSSVM Based on Black Hole Algorithm

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