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	Fireworks algorithm with covariance mutation
	Yu, Chao ; Tan, Ying
	2015
英文摘要	Fireworks algorithm is a novel swarm intelligence algorithm for solving optimization problems-The latest versions include the adaptive fireworks algorithm and the dynamic fireworks algorithm. However, the mutation operator in the former algorithm was ineffective, whereas there was no mutation operator available in the latter algorithm. In this paper, a mutation operator is proposed, dubbed as the covariance mutation (CM) operator. The CM operator utilizes the information of the sparks with better fitness values to generate potential sparks for finding the optima of functions with higher possibility. Therefore, we proposed the fireworks algorithm with covariance mutation (FWACM) and compared it with the most advanced fireworks algorithms. The experimental results show that FWACM is a significant improvement for fireworks algorithms. ? 2015 IEEE.; EI; 1250-1256
语种	英语
出处	IEEE Congress on Evolutionary Computation, CEC 2015
DOI标识	10.1109/CEC.2015.7257032
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/436648]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Yu, Chao,Tan, Ying. Fireworks algorithm with covariance mutation. 2015-01-01.

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