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基于黑洞算法的LSSVM的参数优化
引用本文:王 通,高宪文,蒋子健.基于黑洞算法的LSSVM的参数优化[J].东北大学学报(自然科学版),2014,35(2):170-174.
作者姓名:王 通  高宪文  蒋子健
作者单位:(1.东北大学 信息科学与工程学院, 辽宁 沈阳110819; 2.沈阳工业大学 电气工程学院, 辽宁 沈阳110870)
基金项目:国家自然科学基金重点资助项目(61034005).
摘    要:采用黑洞(BH)算法对最小二乘支持向量机(LSSVM)的惩罚系数C及径向基核函数参数σ进行搜索优化,提高LSSVM的预测性能.黑洞算法模拟自然界黑洞,吸引一定范围内的星体向其运行并吸收它们;算法在运行过程中,始终保持黑洞为最优解,通过星体的运行搜索整个空间.通过基于黑洞算法的LSSVM和基于粒子群(PSO)算法的LSSVM实现对二维函数的预测,并对二者进行了仿真研究.仿真结果证实,黑洞算法可以更好地实现LSSVM参数的优化搜索,且基于黑洞算法的LSSVM方法具有更高的预测精度.

关 键 词:黑洞算法  最小二乘支持向量机  参数搜索  粒子群优化  二维函数  

Parameters Optimizing of LSSVM Based on Black Hole Algorithm
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.
Authors:WANG Tong  GAO Xian wen  JIANG Zi jian
Affiliation:1. School of Information Science & Engineering, Northeastern University, Shenyang 110819, China; 2. School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China.
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.
Keywords:black hole algorithm  least squares support vector machine  parameter selection  particle swarm optimization  two dimensional function
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