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Reliability assessment of component based software systems using fuzzy and ANFIS techniques

机译:使用模糊和ANFIS技术的基于组件的软件系统的可靠性评估

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摘要

Software reliability is one of the most commonly discussed research issue in the field of software engineering. In this paper we evaluate the reliability of component based software using Adaptive Neuro-Fuzzy inference system. The proposed model considers the factors particular to component based software that affects its reliability. The hybrid neural network used in ANFIS is trained using the data set obtained from a survey. This neural network in turn guides the rule base of the fuzzy inference system. Our ANFIS model is validated against the data obtained from survey of various existing component based software designs. An evaluation model based on Mamdani fuzzy inference system is also proposed. The performance analysis of ANFIS model is done by comparing its accuracy in determining correct outputs with that of the FIS model. The ANFIS model is optimized to obtain evaluation near to the empirical results. Experimental results show that ANFIS based evaluation model performs better than the corresponding FIS model.
机译:软件可靠性是软件工程领域中最常讨论的研究问题之一。在本文中,我们使用自适应神经模糊推理系统评估基于组件的软件的可靠性。提出的模型考虑了影响基于组件的软件可靠性的因素。使用从调查中获得的数据集来训练ANFIS中使用的混合神经网络。该神经网络反过来指导模糊推理系统的规则库。我们的ANFIS模型已根据从各种现有的基于组件的软件设计的调查中获得的数据进行了验证。提出了基于Mamdani模糊推理系统的评价模型。 ANFIS模型的性能分析是通过将其确定正确输出的准确性与FIS模型的准确性进行比较来进行的。优化了ANFIS模型以获得接近经验结果的评估。实验结果表明,基于ANFIS的评估模型的性能优于相应的FIS模型。

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