A Hybrid Genetic Programming with Particle Swarm Optimization

摘要：

　　By changing the linear encoding and redefining the evolving rules, particle swarm algorithm is introduced into genetic programming and an hybrid genetic programming with particle swarm optimization (HGPPSO) is proposed.The performance of the proposed algorithm is tested on tow symbolic regression problem in genetic programming and the simulation results show that HGPPSO is better than genetic pro gramming in both convergence times and average convergence genera tions and is a promising hybrid genetic programming algorithm.

关键词： Genetic Programming Particle Swarm Optimization Evolving Rules Symbolic Regression Problem

作者: Feng Qi Yinghong Ma Xiyu Liu Guangyong Ji

作者单位: Shandong Normal University, Jinan 250014, China Yandtai Nanshan University, Yantai 265706, China

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 11-18

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）