计算机工程与应用2016，Vol.52Issue(11)：17-21,5.DOI:10.3778/j.issn.1002-8331.1411-0356
改进PSO-ISVM算法的软件缺陷预测
Software defect prediction based on improved PSO-ISVM algorithm
摘要
Abstract
In order to improve the prediction accuracy of software defects of support vector machine, this paper proposes a software defect prediction model based on improved support vector machine optimized by particle swarm optimization algorithm. The cost penalty coefficient is introduced to define the fitness function for PSO algorithm, and the fitness func-tion is minimized to eliminate redundant information, to improve the software defects prediction accuracy, to find the opti-mal parameters of support vector machine. The validity of model is verified with data set. The simulation results show that the proposed model compared with other common defect prediction methods has improved the software defects pre-diction accuracy and has good nonlinear prediction ability.关键词
缺陷预测/测控软件/粒子群优化/支持向量机Key words
defect prediction/measure and control software/particle swarm optimization/support vector machine分类
信息技术与安全科学引用本文复制引用
张飞..改进PSO-ISVM算法的软件缺陷预测[J].计算机工程与应用,2016,52(11):17-21,5.基金项目
河南省科技厅发展计划(No.142102110088) （No.142102110088）
河南省科技攻关项目(No.122102210430). （No.122102210430）
