%0 Journal Article
%T Using Computing Intelligence Techniques to Estimate Software Effort
%A Jin-Cherng Lin
%A Yueh-Ting Lin
%A Han-Yuan Tzeng
%A Yan-Chin Wang
%J International Journal of Software Engineering & Applications
%D 2013
%I Academy & Industry Research Collaboration Center (AIRCC)
%X In the IT industry, precisely estimate the effort of each software project the development cost and scheduleare count for much to the software company. So precisely estimation of man power seems to be gettingmore important. In the past time, the IT companies estimate the work effort of man power by humanexperts, using statistics method. However, the outcomes are always unsatisfying the management level.Recently it becomes an interesting topic if computing intelligence techniques can do better in this field. Thisresearch uses some computing intelligence techniques, such as Pearson product-moment correlationcoefficient method and one-way ANOVA method to select key factors, and K-Means clustering algorithm todo project clustering, to estimate the software project effort. The experimental result show that usingcomputing intelligence techniques to estimate the software project effort can get more precise and moreeffective estimation than using traditional human experts did.
%K Software Effort Estimation
%K Project Clustering
%K Computing Intelligence
%K Particle Swarm Optimization
%K K-Means Clustering.
%U http://airccse.org/journal/ijsea/papers/4113ijsea04.pdf