title:
 
SEffEst: Effort estimation in software projects using fuzzy logic and neural networks
publication:
 
IJCIS
volume-issue:   5 - 4
pages:   679 - 699
ISSN:
  1875-6883
DOI:
  doi:10.2991/10.1080/18756891.2012.718118 (how to use a DOI)
author(s):
 
Israel González-Carrasco, Ricardo Colomo-Palacios, José Luis López-Cuadrado, Francisco José García Peñalvo
publication date:
 
August 2012
keywords:
 
Fuzzy Logic, Neural Networks, Software Engineering, Effort Estimation
abstract:
 
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.
copyright:
 
© The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/
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