Software Reliability Prediction Model based on Relevance Vector Machine

摘要：

Relevance vector machines have been successfully used in many domains, while their application in software reliability prediction is still quite rare. We proposed an RVM-based model for software reliability prediction, the RVM learning scheme is applied to the failure time data, forcing the network to learn and recognize the inherent internal temporal property of software failure sequence in order to capture the most current feature hidden inside the software failure behavior. We also compare the prediction accuracy of software reliability prediction models based on RVM, SVM and ANN. Experimental results show that our proposed RVM-based software reliability prediction model could achieve a higher prediction accuracy compared with ANN-based and SVM-based models.

关键词： software reliability prediction model relevance vector machine support vector machine artificial neural network

作者: Lou Jun-gang JiangJian-hui Shuai Chun-yan Zhang Rui Jin Ang

作者单位: Department of Computer Science and Technology Tongji University Shanghai,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 229-233

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）