论文标题
使用Swarm Intelligence的软件可靠性模型中参数估计的比较研究
A Comparative Study on Parameter Estimation in Software Reliability Modeling using Swarm Intelligence
论文作者
论文摘要
这项工作着重于两种众所周知的群算法的性能：杜鹃搜索（CS）和萤火虫算法（FA），以估计软件可靠性增长模型的参数。使用粒子群优化（PSO）和蚂蚁菌落优化（ACO）进一步加强了这项研究。根据实际软件故障数据对所有算法进行评估，进行测试并比较获得的结果以显示每种使用的算法的性能。此外，在执行时间和迭代编号的基础上，CS和FA也将相互比较。实验结果表明，CS在估计SRGM的参数方面更有效，并且除了选定的数据集和使用的模型外，除了PSO和ACO外，它的表现优于FA。
This work focuses on a comparison between the performances of two well-known Swarm algorithms: Cuckoo Search (CS) and Firefly Algorithm (FA), in estimating the parameters of Software Reliability Growth Models. This study is further reinforced using Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). All algorithms are evaluated according to real software failure data, the tests are performed and the obtained results are compared to show the performance of each of the used algorithms. Furthermore, CS and FA are also compared with each other on bases of execution time and iteration number. Experimental results show that CS is more efficient in estimating the parameters of SRGMs, and it has outperformed FA in addition to PSO and ACO for the selected Data sets and employed models.
