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http://dx.doi.org/10.3745/KIPSTD.2009.16D.5.729

Estimation of software project effort with genetic algorithm and support vector regression  

Kwon, Ki-Tae (강릉대학교 컴퓨터공학과)
Park, Soo-Kwon (강릉대학교 컴퓨터공학과)
Publication Information
The KIPS Transactions:PartD / v.16D, no.5, 2009 , pp. 729-736 More about this Journal
Abstract
The accurate estimation of software development cost is important to a successful development in software engineering. Until recent days, the model using regression analysis based on statistical algorithm and machine learning method have been used. However, this paper estimates the software cost using support vector regression, a sort of machine learning technique. Also, it finds the best set of optimized parameters applying genetic algorithm. The proposed GA-SVR model outperform some recent results reported in the literature.
Keywords
Support Vector Regression; Software Cost Estimation; Machine Learning; Gentic Algorithm; Parameters;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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