期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2013
卷号：4
期号：1
DOI：10.14569/IJACSA.2013.040124
出版社：Science and Information Society (SAI)
摘要：Software cost estimation is the process of predicting the effort required to develop a software system. The basic input for the software cost estimation is coding size and set of cost drivers, the output is Effort in terms of Person-Months (PM’s). Here, the use of support vector regression (SVR) has been proposed for the estimation of software project effort. We have used the COCOMO dataset and our results are compared to Intermediate COCOMO as well as to MOPSO model results for this dataset. It has been observed from the simulation that SVR outperforms other estimating techniques. This paper provides a comparative study on support vector regression (SVR), Intermediate COCOMO and Multiple Objective Particle Swarm Optimization (MOPSO) model for estimation of software project effort. We have analyzed in terms of accuracy and Error rate. Here, data mining tool Weka is used for simulation
