文章基本信息

标题：Improved Genetic Programming Algorithm Applied to Symbolic Regression and Software Reliability Modeling
本地全文：下载
作者：Yongqiang ZHANG ; Huifang CHENG ; Ruilan YUAN 等
期刊名称：Journal of Software Engineering and Applications
印刷版ISSN：1945-3116
电子版ISSN：1945-3124
出版年度：2009
卷号：2
期号：5
页码：354-360
DOI：10.4236/jsea.2009.25047
出版社：Scientific Research Publishing
摘要：The present study aims at improving the ability of the canonical genetic programming algorithm to solve problems, and describes an improved genetic programming (IGP). The proposed method can be described as follows: the first inves-tigates initializing population, the second investigates reproduction operator, the third investigates crossover operator, and the fourth investigates mutation operation. The IGP is examined in two domains and the results suggest that the IGP is more effective and more efficient than the canonical one applied in different domains.
关键词：Improved Genetic Programming; Symbolic Regression; Software Reliability Model