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

DOI

10.1080/18756891.2012.718118How to use a DOI?

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

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Israel González-Carrasco
AU  - Ricardo Colomo-Palacios
AU  - José Luis López-Cuadrado
AU  - Francisco José García Peñalvo
PY  - 2012
DA  - 2012/08/01
TI  - SEffEst: Effort estimation in software projects using fuzzy logic and neural networks
JO  - International Journal of Computational Intelligence Systems
SP  - 679
EP  - 699
VL  - 5
IS  - 4
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2012.718118
DO  - 10.1080/18756891.2012.718118
ID  - González-Carrasco2012
ER  -