Electrical and Computer Engineering Publications
Improving the COCOMO Model Using a Neuro-Fuzzy Approach
Document Type
Article
Publication Date
1-2007
Volume
7
Issue
1
Journal
Applied Soft Computing
First Page
29
URL with Digital Object Identifier
10.1016/asoc.2005.06.007
Last Page
40
Abstract
Accurate software development cost estimation is important for effective project management such as budgeting, project planning and control. So far, no model has proved to be successful at effectively and consistently predicting software development cost. A novel neuro-fuzzy Constructive Cost Model (COCOMO) is proposed for software cost estimation. This model carries some of the desirable features of a neuro-fuzzy approach, such as learning ability and good interpretability, while maintaining the merits of the COCOMO model. Unlike the standard neural network approach, the proposed model can be interpreted and validated by experts, and has good generalization capability. The model deals effectively with imprecise and uncertain input and enhances the reliability of software cost estimates. In addition, it allows input to have continuous rating values and linguistic values, thus avoiding the problem of similar projects having large different estimated costs. A detailed learning algorithm is also presented in this work. The validation using industry project data shows that the model greatly improves estimation accuracy in comparison with the well-known COCOMO model.
Citation of this paper:
@article{DBLP:journals/asc/HuangHRC07, author = {Xishi Huang and Danny Ho and Jing Ren and Luiz Fernando Capretz}, title = {Improving the COCOMO model using a neuro-fuzzy approach}, journal = {Appl. Soft Comput.}, volume = {7}, number = {1}, year = {2007}, pages = {29-40}, ee = {http://dx.doi.org/10.1016/j.asoc.2005.06.007}, bibsource = {DBLP, http://dblp.uni-trier.de} }
