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所属单位：航空学院

发表刊物：Commun. Comput. Info. Sci.

摘要：In order to improve the abilities of global exploration and local exploitation for the fireworks explosion algorithm (FA), the opposition-based learning method is introduced to generate the opposition-based population and to expand the exploration range of the FA. In addition, a computing method of adaptive adjustment of explosion radius is proposed based on the fitness differences of the individuals in the population. These above strategies are integrated to form an adaptive fireworks explosion optimization algorithm with opposition-based learning. The presented FA is experimented with other four swarm intelligence optimization algorithms, and the results show that our improved FA clearly outperforms the others in the performance of convergence and accuracy. © 2018, Springer Nature Singapore Pte Ltd.

ISSN号：1865-0929

是否译文：否

发表时间：2018-01-01

合写作者：王立平,Xie, Chengwang

通讯作者：陈仁文