A Hybrid Intelligent Model for Software Cost Estimation

Authors

Wei Lin Du, Western UniversityFollow
Luiz Fernando Capretz, University of Western OntarioFollow
Ali Bou Nassif, Western UniversityFollow
Danny Ho, NFA-EstimationFollow

Document Type

Article

Publication Date

2013

Volume

9

Issue

11

Journal

Journal of Computer Science

First Page

1506

URL with Digital Object Identifier

http://dx.doi.org/10.3844/jcssp.2013.1506.1513

Last Page

1513

Abstract

Accurate software development effort estimation is critical to the success of software projects. Although many techniques and algorithmic models have been developed and implemented by practitioners, accurate software development effort prediction is still a challenging endeavor in the field of software engineering, especially in handling uncertain and imprecise inputs and collinear characteristics. In this paper, a hybrid intelligent model combining a neural network model integrated with fuzzy model (neuro-fuzzy model) has been used to improve the accuracy of estimating software cost. The performance of the proposed model is assessed by designing and conducting evaluation with published project and industrial data. Results have shown that the proposed model demonstrates the ability of improving the estimation accuracy by 18% based on the Mean Magnitude of Relative Error (MMRE) criterion.