SEffEst: Effort estimation in software projects using fuzzy logic and neural networks

被引:11
|
作者
Gonzalez-Carrasco, Israel [1 ]
Colomo-Palacios, Ricardo
Luis Lopez-Cuadrado, Jose
Garcia Penalvo, Francisco Jose [2 ]
机构
[1] Univ Carlos III Madrid, Dept Comp Sci, Leganes 29811, Madrid, Spain
[2] Univ Salamanca, Dept Informat & Automat, E-37008 Salamanca, Spain
关键词
Fuzzy Logic; Neural Networks; Software Engineering; Effort Estimation; GENETIC ALGORITHMS; COST ESTIMATION; SIZE; OPTIMIZATION; FRAMEWORK; WEIGHTS; NOISE; MODEL;
D O I
10.1080/18756891.2012.718118
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Academia and practitioners confirm that software project effort prediction is crucial for an accurate software project management. However, software development effort estimation is uncertain by nature. Literature has developed methods to improve estimation correctness, using artificial intelligence techniques in many cases. Following this path, this paper presents SEffEst, a framework based on fuzzy logic and neural networks designed to increase effort estimation accuracy on software development projects. Trained using ISBSG data, SEffEst presents remarkable results in terms of prediction accuracy.
引用
收藏
页码:679 / 699
页数:21
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