• DocumentCode
    3521166
  • Title

    Software Reliability Prediction Model Based on Relevance Vector Machine

  • Author

    Zheng, Qiuhong

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Technol., ZheJiang Wanli Univ., Ningbo, China
  • fYear
    2010
  • fDate
    1-3 Nov. 2010
  • Firstpage
    317
  • Lastpage
    320
  • Abstract
    Relevance vector machines have been successfully used in many domains, while their application in software reliability prediction is still quite rare. In this work, we propose to apply support vector regression (SVR) to build software reliability prediction model (RVMSRPM). We also compare the prediction accuracy of software reliability prediction models based on RVM, SVM, ANN and three traditional NHPP models. Experimental results show that our proposed RVM-based software reliability prediction model could achieve a higher prediction accuracy compared with these models.
  • Keywords
    neural nets; prediction theory; regression analysis; software reliability; support vector machines; relevance vector machine; software reliability prediction model; support vector regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantics Knowledge and Grid (SKG), 2010 Sixth International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-8125-5
  • Electronic_ISBN
    978-0-7695-4189-1
  • Type

    conf

  • DOI
    10.1109/SKG.2010.49
  • Filename
    5663537