Software fault prediction based on grey neural network

Peng Zhang, Yu-tong Chang
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引用次数: 8

Abstract

Considering determining the number of software fault is an uncertain non-linear problem with only small sample, a novel software fault prediction method based on grey neural network is put forward. Firstly, constructing the grey neural network topological structure according the small sample sequence is necessary, and then the network learning algorithm is discussed. Finally, the grey neural network prediction model based on the grey theory and artificial neural network is proposed. The sample fault sequences of some software project are used to verify the precision of this method. Comparison with GM(1,1), the proposed model can reduce the prediction relative error effectively.
基于灰色神经网络的软件故障预测
考虑到软件故障数量的确定是一个小样本不确定的非线性问题,提出了一种基于灰色神经网络的软件故障预测方法。首先根据小样本序列构造灰色神经网络拓扑结构,然后讨论了网络学习算法。最后,提出了基于灰色理论和人工神经网络的灰色神经网络预测模型。以某软件工程的故障序列为例,验证了该方法的精度。与GM(1,1)模型相比,该模型能有效降低预测相对误差。
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