Improving Estimative Capability of Software Development Effort using Radial Basis Function Network


The KIPS Transactions:PartD, Vol. 8, No. 5, pp. 581-586, Oct. 2001
10.3745/KIPSTD.2001.8.5.581,   PDF Download:

Abstract

An increasingly important facet of software development is the ability to estimate the associated cost and effort of development early in the development life cycle. In spite of the most generally used procedures for estimation of the software development effort and cost were linear regression analysis. As a result of the software complexity and various development environments, the software effort and cost estimates that are grossly inaccurate. The application of nonlinear methods hold the greatest promise for achieving this objective. Therefore, this paper presents an RBF (radial basis function) network model that is able to represent the nonlinear relation for software development effort. The research describes appropriate RBF network modeling in the context of a case study for 24 software development projects. Also, this paper compared the RBF network model with a regression analysis model. The RBF network model is the most accuracy of all.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
S. U. Lee, Y. M. Park, J. H. Park, "Improving Estimative Capability of Software Development Effort using Radial Basis Function Network," The KIPS Transactions:PartD, vol. 8, no. 5, pp. 581-586, 2001. DOI: 10.3745/KIPSTD.2001.8.5.581.

[ACM Style]
Sang Un Lee, Young Mok Park, and Jae Heung Park. 2001. Improving Estimative Capability of Software Development Effort using Radial Basis Function Network. The KIPS Transactions:PartD, 8, 5, (2001), 581-586. DOI: 10.3745/KIPSTD.2001.8.5.581.