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An introduction to few soft computing techniques to predict software quality

机译:介绍几种预测软件质量的软计算技术

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Soft computing is combination of various computation methodologies. It is being widespread among various researchers and organizations due to increase in demand of software quality and changing business rules. Soft computing techniques are used to produce results and analysis that measures capricious phenomenon of human mind like partial truth, uncertainty of beliefs and approximation. The paper presents brief overview of soft computing techniques like Artificial Neural Networks (ANN), Fuzzy Logic systems (FLS), Radial Basis Function (RBF) and many more. A soft computing framework has been proposed to predict quality of software by calculating error in weights of different nodes of Multi-layer perceptron (MLP) neural network with the help of Neuphron open source framework.
机译:软计算是各种计算方法的组合。由于对软件质量的需求增加和不断变化的业务规则,它在各种研究人员和组织中得到了广泛传播。软计算技术用于产生结果和分析,以测量人脑中反复无常的现象,例如部分真实性,信念的不确定性和近似性。本文简要概述了诸如人工神经网络(ANN),模糊逻辑系统(FLS),径向基函数(RBF)等软计算技术。借助Neuphron开源框架,已经提出了一种软计算框架来预测软件质量,方法是通过计算多层感知器(MLP)神经网络的不同节点的权重误差来预测软件质量。

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