Neural network based models for software effort estimation: a review

被引：73

作者：

Dave, Vachik S. ^{[1
]}

Dutta, Kamlesh ^{[1
]}

机构：

[1] Natl Inst Technol, Dept Comp Sci & Engn, Hamirpur, HP, India

来源：

ARTIFICIAL INTELLIGENCE REVIEW | 2014年 / 42卷 / 02期

关键词：

Neural networks; Effort estimation; Accuracy; Reliability; COST ESTIMATION; SIZE;

D O I：

10.1007/s10462-012-9339-x

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Prediction of software development effort is the key task for the effective management of any software industry. The accuracy and reliability of prediction mechanisms is also important. Neural network based models are competitive to traditional regression and statistical models for software effort estimation. This comprehensive article, covers various neural network based models for software estimation as presented by various researchers. The review of twenty-one articles covers a range of features used for effort prediction. This survey aims to support the research for effort prediction and to emphasize capabilities of neural network based model in effort prediction.

引用

页码：295 / 307

页数：13

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