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	RANDOM BLACK HOLE PARTICLE SWARM OPTIMIZATION AND ITS APPLICATION
	Zhang, Junqi ; Liu, Kun ; Tan, Ying ; He, Xingui
	2007
关键词	PSO Black Hole Swarm intelligence Spam detection SELECTION
英文摘要	This paper introduces a novel particle swarm optimization algorithm based on the concept of black holes in physics, called random black hole particle swarm optimization (RBH-PSO) for the first time. In each dimension of a particle, we randomly generate a black hole located nearest to the best particle of the swarm in current generation and then randomly pull particles of the swarm into the black hole with a probability p. By this mechanism of random black hole, we can give all the particles another interesting direction to converge as well as another chance to fly out of local minima when a premature convergence happens. Several experiments on fifteen benchmark test functions are conducted to demonstrate that the proposed RBH-PSO algorithm is able to speedup the evolution process distinctly and improve the performance of global optimizer greatly. Finally, an actual application of the proposed algorithm to spam detection is conducted then compared to other three current methods.; Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic; Telecommunications; CPCI-S(ISTP); 0
语种	英语
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/406438]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhang, Junqi,Liu, Kun,Tan, Ying,et al. RANDOM BLACK HOLE PARTICLE SWARM OPTIMIZATION AND ITS APPLICATION. 2007-01-01.

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