DocumentCode
2854852
Title
Comparison between regression analysis and artificial neural network in project selection
Author
Olanrewaju, O.A. ; Jimoh, A.A. ; Kholopane, P.A.
Author_Institution
Dept. of Ind. Eng., Tshwane Univ. of Technol., Pretoria, South Africa
fYear
2011
fDate
6-9 Dec. 2011
Firstpage
738
Lastpage
741
Abstract
A common problem faced by managers is that of project selection, to decide which project out of the lots should be undertaken. This paper aims at comparing results of the application of two approaches - respectively regression analysis, a parametric method and artificial neural network, a non-parametric technique. To demonstrate these methods, the models were illustrated using Oral, Kettani and Lang´s data on 37 R&D projects for their success. From statistical analysis, it was discovered that artificial neural network showed superiority to deciding how projects should be ranked and selected.
Keywords
neural nets; production engineering computing; project management; regression analysis; artificial neural network; parametric method; project selection; regression analysis; statistical analysis; Artificial neural networks; Biological neural networks; Biological system modeling; Economics; Mathematical model; Neurons; Regression analysis; Project selection; artificial neural network; regression analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference on
Conference_Location
Singapore
ISSN
2157-3611
Print_ISBN
978-1-4577-0740-7
Electronic_ISBN
2157-3611
Type
conf
DOI
10.1109/IEEM.2011.6118014
Filename
6118014
Link To Document