Software reliability prediction by soft computing techniques

N. Raj Kiran; V. Ravi

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Software reliability prediction by soft computing techniques

机译：基于软计算技术的软件可靠性预测

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摘要

With a brief introduction to software reliability issues, a detailed literature review is provided on software reliability modeling and forecasting. Various software reliability prediction techniques available in the literature are described. By exploiting the features of each of such constituent models, four ensemble models are developed out of which three are linear and based on statistical averaging and one is non-linear in nature and based on back propagation neural network. A time series data-based experimental design is considered to apply both the constituent and ensemble models separately. It is observed that the non-linear ensemble model outperforms all other models from the perspective of normalized root mean square error.

机译：通过对软件可靠性问题的简要介绍，对软件可靠性建模和预测进行了详细的文献综述。描述了文献中可用的各种软件可靠性预测技术。通过利用这些组成模型的特征，开发了四个集成模型，其中三个是线性的，基于统计平均，一个是非线性的，基于反向传播神经网络。基于时间序列数据的实验设计被认为是分别应用成分模型和集成模型。从归一化均方根误差的角度来看，非线性集成模型优于所有其他模型。

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来源
《Quality Control and Applied Statistics》 |2008年第6期|627-628|共2页
作者
N. Raj Kiran; V. Ravi;
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作者单位

Institute for Development and Research in Banking Technology, Castle Hills Road #1, Masab Tank, Hyderabad 500 057, Andhra Pradesh, India;

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原文格式 PDF
正文语种英语
中图分类概率论、数理统计的应用;
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Software reliability prediction by soft computing techniques

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