[1]杨晓琴.基于改进蝙蝠算法的软件缺陷预测模型[J].计算机技术与发展,2018,28(12):74-78.[doi:10．3969/j． issn．1673－629X．2018．12．016]
　YANG Xiaoqin.Software Defect Prediction Model Based on Improved Bat Algorithm[J].,2018,28(12):74-78.[doi:10．3969/j． issn．1673－629X．2018．12．016]
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基于改进蝙蝠算法的软件缺陷预测模型()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年12期
页码:
74-78
栏目:
智能、算法、系统工程
出版日期:
2018-12-10

文章信息/Info

Title:
Software Defect Prediction Model Based on Improved Bat Algorithm
文章编号:
1673－629X(2018)12－0074－05
作者:
杨晓琴
太原广播电视大学
Author(s):
YANG Xiao－qin
Taiyuan Radio and TV University，Taiyuan 030002，China
关键词:
支持向量机;  软件缺陷预测;  莱维飞行;  蝙蝠算法
Keywords:
support vector machine; software defect prediction; Levy flight; bat algorithm
分类号:
TP301
DOI:
10．3969/j． issn．1673－629X．2018．12．016
摘要:
软件缺陷预测模型因为软件规模持续扩大以及安全性要求越来越高,变得越来越重要。支持向量机(SVM)模型突出优点是它具有较强的非线性分类能力,所以在软件缺陷预测应用非常广泛。但是,SVM模型缺乏有效的方法来确定最佳参数,以至于不能达到理想的准确度。所以,提高SVM模型的参数,提高SVM模型的软件缺陷预测能力成为了研究热点。蝙蝠算法是一种启发式搜索算法,它模型简单,易于实现,但是却易陷入局部最优,因此采用加入莱维飞行的蝙蝠算法对SVM模型的参数选择进行优化。为了测试这个新模型的性能,仿真实验使用了一些软件缺陷预测的公共数据集,然后将结果与传统的启发式算法进行比较。实验结果表明,LBA-SVM模型的分类能力优于其他方法。
Abstract:
The software defect prediction model is becoming more and more important because of its continuous expansion of software scale and the increasing security requirements． The protruding advantage of support vector machine (SVM) model is that it has strong nonlinear classification，so it is widely used in software defect prediction． However，the SVM model lacks effective methods to determine the optimal parameters，so that it cannot achieve the ideal accuracy． Therefore，to improve the parameters and the ability of software de- fect prediction in SVM model has become a hot research topic． Bat algorithm is a heuristic search algorithm，which is simple and easy to implement，but it is easy to fall into local optimal． Therefore we use the bat algorithm with Levy flight to optimize parameters on the SVM model． In order to test the performance of this new model，a number of common data sets are used to predict software defects． The simulation results are compared with the other five methods，which show that the classification of the LBA－SVM model is better than that of other methods．

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更新日期/Last Update: 2018-12-10