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Software Reliability Prediction Model Based on Relevance Vector Machine

机译:基于关联向量机的软件可靠性预测模型

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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.
机译:相关向量机已经在许多领域成功使用,但是它们在软件可靠性预测中的应用仍然很少。在这项工作中,我们建议应用支持向量回归(SVR)来建立软件可靠性预测模型(RVMSRPM)。我们还比较了基于RVM,SVM,ANN和三个传统NHPP模型的软件可靠性预测模型的预测准确性。实验结果表明,我们提出的基于RVM的软件可靠性预测模型与这些模型相比可以实现更高的预测精度。

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