Comparison of artificial neural network and regression models for estimating software development ef

2025-02-14 Classification：language Click()
Author：Heiat, A

Article Title：Comparison of artificial neural network and regression models for estimating software development effort

Abstract：
Estimating the amount of effort required for developing an information system is an important project management concern. In recent years, a number of studies have used neural networks in various stages of software development. This study compares the prediction performance of multilayer perceptron and radial basis function neural networks to that of regression analysis. The results of the study indicate that when a combined third generation and fourth generation languages data set were used, the neural network produced improved performance over conventional regression analysis in terms of mean absolute percentage error. (C) 2002 Elsevier Science B.V. All rights reserved.

Keywords: artificial neural network; regression models; software development effort

DOI: 10.1016/S0950-5849(02)00128-3

Source：INFORMATION AND SOFTWARE TECHNOLOGY

Welcome to correct the error, please contact email: humanisticspider@gmail.com

Related Reading

Articulatory movements in adolescents: Evidence for protracted development of speech motor control pArticulatory movements in adolescents: Evidence for protracted development of speech motor control p
Direct magnitude estimation and interval scaling of naturalness and severity in tracheoesophageal (TDirect magnitude estimation and interval scaling of naturalness and severity in tracheoesophageal (T
Having a laugh at work: how humour contributes to workplace cultureHaving a laugh at work: how humour contributes to workplace culture
Dyadic versus individual storytelling by preschool childrenDyadic versus individual storytelling by preschool children