基于SVR的军用装备软件可靠性模型研究  

Research on Military Equipment Software Reliability Model Based on SVR

作　　者：马振宇 张威[1] 吴纬[2] 刘福胜[1] 高飞 MA Zhen-yu;ZHANG Wei;WU Wei;LIU Fu-sheng;GAO Fei(Academy of Armored Force Engineering, Beijing 100072, China;Beijing Special Vehicle Research Institute,Beijing 100072,China;Unit 95942 of PLA, Wuhan 430300, China)

机构地区：[1]装甲兵工程学院 [2]北京特种车辆研究所 [3]中国人民解放军95942部队

出　　处：《微电子学与计算机》2018年第7期72-77,共6页Microelectronics & Computer

摘　　要：在软件可靠性建模时,有效的提高可靠性的预测精度,对于指导可靠性测试,提高军用装备软件可靠性具有十分重要的作用.从特种车辆软件测评中心收集了相关数据.将支持向量回归算法应用到军用装备软件的可靠性模型中,并与13种其他机器学习算法模型进行比较.结果表明SVR算法提高了军用软件可靠性预测准确率,分别在均方根误差、平均绝对误差、相对平方根误差、相对绝对误差这四个方面体现出来.In the process of software reliability modeling, it is very important to effectively improve the prediction accuracy of reliability, which can guide the reliability test and improve the reliability of military equipment software. Related data is collected from Special Vehicles Software Assessment Center. It applies support vector regression to military equipment software reliability model and compare to other machine learning algorithms model. The result illustrates that the SVR algorithm can improve the accuracy of military software reliability prediction, which is reflected in the following four aspects： root mean square error, mean absolute error, root relative square error, relative absolute error.

关 键 词：可靠性测试 缺陷密度 SVR 可靠性预测 

分 类 号：TP311.5[自动化与计算机技术—计算机软件与理论]