Research on Software Reliability Based on Forecasting Model Combined by LS-SVM and Markov Chain

Xiao Mei Zhu; Qun Yan Zhang

doi:10.4028/www.scientific.net/AMM.197.542

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 197Research on Software Reliability Based on...

Research on Software Reliability Based on Forecasting Model Combined by LS-SVM and Markov Chain

Abstract:

To improve the accuracy of prediction on software failure data, one combine forecasting model is proposed based on least square support vector machine (LS-SVM) and Markov chain. First, LS-SVM optimized by simulated annealing algorithm (SA) is adopted to establish the time series forecasting model on software failure data. Then, in order to improve the prediction accuracy, the prediction interval is narrowed by means of Markov chain. Finally, after applying the combination forecasting model to the predicting of one commercial software failure data, the results indicate that the model has a certain precision and reliability.

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Periodical:

Applied Mechanics and Materials (Volume 197)

Pages:

542-546

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.197.542

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Online since:

September 2012

Authors:

Xiao Mei Zhu, Qun Yan Zhang

Keywords:

Forecasting, Least Squares Support Vector Machines (Ls-SVM), Markov Chain, Software Reliability

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