Assessing RBFN-based software cost estimation models

TitreAssessing RBFN-based software cost estimation models
Publication TypeConference Paper
Year of Publication2013
AuthorsIdri, Aa, Hassani, Aa, Abran, Ab
Conference NameProceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE

This paper is concerned with the design of the neural networks approach, especially Radial Basis Function Neural (RBFN) networks, for software effort estimation models. The study firstly focuses on the construction of the RBFN middle layer composed of receptive fields, using two clustering techniques: hard C-means and fuzzy C-means. Thereafter, we evaluate and compare the performance of effort estimation models that use an RBFN construction-based either on hard or fuzzy C-means. This study uses the ISBSG dataset and confirms the usefulness of an RBFN-based on fuzzy C-means for software effort estimation. Copyright © 2013 by Knowledge Systems Institute Graduate School.




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