Gene Expression Programming Based on Diversified Development Strategy

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收藏 2011-09-30

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Journal of Jilin University(Information Science Ed 2010, 28(04) 396- DOI: ISSN: 1671-5896 CN: 22-1344/TN

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	Keywords
	gene expression programming (GEP)
	diversity
	genetic operator
	function mining
	Authors
	PubMed

Gene Expression Programming Based on Diversified Development Strategy

WU Jiang1|LI Tai-yong1|JIANG Yue2|LI Zi-li1|LIU Yang-yang1

1盨chool of Economic Information Engineering, Southwestern University of Finance and Economics, Chengdu 610074, China|2盨chool of Computer Science and Technology, Southwest University for Nationalities, Chengdu 610041, China

Abstract： In order to reduce the rate of premature convergence and to escape from local optimum, GEP(Gene Expression Programming) based on diversified development strategy is proposed, which assigns the population with different development strategies to enhance the optimizing ability of GEP through GSBS（Gene Space Balance Strategy), ACMO（Adaptive Crossover and Mutation Operators) and obsolete operator (OBSO). Experiments on function mining show that all of strategies play roles of mining. Compared with the result of GEP. The number of average evolution generations is decreased by 11%, evolution time is decreased by 8%, and the success rate is increased by 20%.

Keywords： gene expression programming (GEP) diversity genetic operator function mining

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Email: wuj_t@swufe.edu.cn。

http://xuebao.jlu.edu.cn/xxb/EN/abstract/abstract8552.shtml