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软件风险评估量化分析研究
引用本文:闫秋粉,南振岐,姚尔果,薛小虎.软件风险评估量化分析研究[J].计算机工程与设计,2012,33(4):1581-1585.
作者姓名:闫秋粉  南振岐  姚尔果  薛小虎
作者单位:1. 西北师范大学数学与信息科学学院,甘肃兰州,730070
2. 新疆乌鲁木齐市军区测绘信息中心,新疆乌鲁木齐,830000
基金项目:甘肃省自然科学基金项目(1010RJZA019)
摘    要:为解决软件风险评估完全凭借专家经验产生的主观性和模糊性问题,提出了基于进化神经网络模型的软件风险定量评估方法.通过研究软件风险评估过程,提出了软件风险评估指标体系模型,同时运用模糊理论将风险因素量化以此作为进化神经网络的输入值.将改进的粒子群算法(PSO)、BP神经网络相结合,构建了基于改进BP神经网络的进化神经网络模型.对提出的模型和改进的算法进行模拟仿真实验,实验结果表明了该方法对软件风险评估量化分析的可行性.

关 键 词:软件风险定量评估  风险评估指标体系  模糊理论  进化神经网络模型  BP神经网络  粒子群算法

Quantitative analysis research for software risk evaluation
YAN Qiu-fen , NAN Zhen-qi , YAO Er-guo , XUE Xiao-hu.Quantitative analysis research for software risk evaluation[J].Computer Engineering and Design,2012,33(4):1581-1585.
Authors:YAN Qiu-fen  NAN Zhen-qi  YAO Er-guo  XUE Xiao-hu
Affiliation:1.College of Mathematics and Information Science,Northwest Normal University,Lanzhou 730070,China; 2.Military Mapping Information Center of Xinjiang,Urumqi 830000,China)
Abstract:To solve the subjectivity and fuzziness question of software risk assessment completely depending on experts’ experience,the quantitative evaluation method for software risk based on evolutionary neural network model is proposed.Firstly,by researching software risk evaluation process,the software risk evaluation index system is proposed,at the same time risk factors by applying fuzzy theory is quantified,as evolutionary neural network input value.Secondly,evolutionary neural network model based on improved back propagation(BP) neural network is constructed,combining the improved particle swarm optimization algorithm(PSO) and back propagation(BP) neural network.Finally,the feasibility of the method on quantitative analysis for software risk evaluation is validated with practical application,by simulating the model and the improved algorithm.
Keywords:quantitative evaluation for software risk  risk evaluation index system  fuzzy theory  evolutionary neural network model  back propagation(BP) neural network  particle swarm optimization algorithm(PSO)
本文献已被 CNKI 万方数据 等数据库收录!
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