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基于EM-GA改进贝叶斯网络的研究及应用*
引用本文:金俊丽,赵川,杨洁.基于EM-GA改进贝叶斯网络的研究及应用*[J].计算机应用研究,2010,27(4):1360-1362.
作者姓名:金俊丽  赵川  杨洁
作者单位:1. 淮海工学院,理学院,江苏,连云港,222005
2. 重庆大学,机械工程学院,重庆,400030
3. 重庆通信学院,重庆,400035
基金项目:国家教育部“新世纪优秀人才支持计划”资助项目(NCET-07-0908)
摘    要:为了解决软件风险分析中可能出现的数据不完整以及影响因素间关系复杂的问题,提出了一种改进贝叶斯网络的软件项目风险分析方法。将遗传算法和EM算法相结合得到EM-GA算法,利用EM-GA算法对软件项目分析过程中贝叶斯网络结构中的参数进行学习,同时优化网络结构,通过实例验证了该方法的有效性及可行性。

关 键 词:贝叶斯网络    EM-GA算法    软件项目    风险分析

Research on Bayesian network improved by EM-GA and its application
JIN Jun-li,ZHAO Chuan,YANG Jie.Research on Bayesian network improved by EM-GA and its application[J].Application Research of Computers,2010,27(4):1360-1362.
Authors:JIN Jun-li  ZHAO Chuan  YANG Jie
Affiliation:(1.College of Science, Huaihai Institute of Technology, Lianyungang Jiangsu 222005, China; 2. College of Mechanical Engineering, Chongqing University, Chongqing 400030, China; 3. Chongqing Communication College, Chongqing 400035, China )
Abstract:In order to solve the problem of incomplete data and complex relations among influencing factors which may appear in the software risk analysis, this paper presented a software project risk analysis process based on Bayesian networks which has been improved. Firstly, presented a EM-GA algorithm based on genetic algorithm. Then, used the algorithm to optimize the Bayesian networks structures and solve Bayesian parameter learning. Finally, the experiment results show this algorithm provide a new method for software project risk analysis process.
Keywords:Bayesian networks  EM-GA algorithm  software project  risk analysis
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