BS-GEP Algorithm for Prediction of Software Failure Series

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@Article{Zhang:2012:Jsoftware,

• author = "Yongqiang Zhang and Jing Xiao and Shengjuan Sun",
• title = "BS-GEP Algorithm for Prediction of Software Failure Series",
• journal = "Journal of Software",
• year = "2012",
• volume = "7",
• number = "1",
• pages = "243--248",
• month = jan,
• keywords = "genetic algorithms, genetic programming, gene expression programming, SBSE, BS-GEP, complexity analysis, convergence analysis, software failure, time series prediction",
• ISSN = "1796217X",
• URL = "http://www.jsoftware.us/index.php?m=content&c=index&a=show&catid=55&id=1084",
• URL = "http://www.jsoftware.us/vol7/jsw0701-33.pdf",
• broken = "http://ojs.academypublisher.com/index.php/jsw/article/view/5146",
• broken = "http://www.doaj.org/doaj?func=openurl\&genre=article\&issn=1796217X\&date=2012\&volume=7\&issue=1\&spage=243",
• size = "6 pages",
• abstract = "This paper introduces GEP(Gene Expression Programming) fundamental. Aimed at prediction of software failure sequence, an improved GEP(GEP based on Block Strategy, BS-GEP) is presented, in which the population is divided into several blocks according to the individual fitness of each generation and the genetic operators are reset differently in each block to guarantee the genetic diversity. The algorithm complexity and convergence of BS-GEP is analysed in the paper. Furthermore, BS-GEP is applied in the solution of prediction in software failure sequence. The simulation results show that the model found by BS-GEP, which is proved widely used for many other time series, is more accurate than the one of classic GEP.",
• bibsource = "OAI-PMH server at www.doaj.org",
• language = "eng",
• oai = "oai:doaj-articles:cce5bee368f9a6cd7fa22ef0f44dc45b",

}

Genetic Programming entries for Yongqiang Zhang Jing Xiao Shengjuan Sun

Citations