Software Effort Estimation Using Radial Basis Function Neural Networks

摘要

One of the biggest challenges that software developers face is to make an accurate estimate of theproject effort. Radial basis function neural networks have been used to software effort estimation in this workusing NASA dataset. This paper evaluates and compares radial basis function versus a regression model. Theresults show that radial basis function neural network have obtained less Mean Square Error than the regressionmethod.