基于AGA-LVQ神经网络的软件可靠性预测模型研究  

Research of Software Reliability Prediction Model Based on AGA-LVQ

作　　者：乔辉[1] 周雁舟[1] 邵楠[1] 高杨[1] 粟登银[1] 

机构地区：[1]中国人民解放军信息工程大学电子技术学院,郑州450004

出　　处：《计算机科学》2013年第1期179-182,共4页Computer Science

摘　　要：针对当前大多数软件可靠性预测模型预测准确率不高等问题,利用LVQ神经网络的非线性运算能力和自适应遗传算法(AGA)的参数寻优能力,提出了一种基于AGA-LVQ的软件可靠性预测模型。首先对待预测的数据用主成分分析(PCA)等方法进行预处理以降低维度,去除冗余和错误数据,然后根据自适应遗传算法来计算最优的LVQ神经网络初始权值向量,最后运用LVQ神经网络进行软件可靠性预测实验。通过与传统方法的对比,证明该方法具有较高的预测准确率。The prediction accuracy of most current software reliability prediction models is not high.This paper put forward a software reliability prediction model based on AGA-LVQ,which takes advantage of non-linear computing power of the learning vector quantization（LVQ） neural network and parameter optimization capability of the adaptive genetic algorithm（AGA）.Firstly,principle components analysis（PCA） preprocessing was used to reduce the dimension of the metrics and remove the redundancy and error data.Secondly,AGA was used to calculate the optimal initial vector weights of the LVQ neural network.Lastly,LVQ neural network was used to do the software reliability prediction experiments.The experiment results indicate that the method has a higher prediction precision than the traditional software reliability prediction model.

关 键 词：软件可靠性预测 模式识别 LVQ神经网络 自适应遗传算法 主成分分析 

分 类 号：TP311.5[自动化与计算机技术—计算机软件与理论]