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Software reliability prediction based on learning vector quantization neutral network
QIAO Hui ZHOU Yan-zhou SHAO Nan
Journal of Computer Applications
2012, 32 (05):
1436-1438.
The application of traditional software prediction model has poor generalized performance. This paper put forward a software reliability prediction model based on Learning Vector Quantization (LVQ) neural network. First, this paper analyzed the structure characteristics of LVQ neural network and its relation with software reliability prediction. Then the network was used to predict the software reliability. In the end, the authors confirmed the algorithm through multiple simulation experiments under the Matlab environment and the data from Metrics Data Program (MDP) database of National Aeronautics and Space Administration (NASA) of USA. The experimental results indicate that the method is feasible and has a higher prediction precision than the traditional software prediction method.
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