Project Selection: Artificial Neural Network Approach
Science Journal of Business and Management
Volume 1, Issue 3, October 2013, Pages: 37-42
Received: Aug. 7, 2013; Published: Oct. 20, 2013
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Olanrewaju Oludolapo Akanni, Industrial Engineering Department, Tshwane University of Technology, Pretoria, South Africa
Jimoh Abdul-Ganiyu Adisa, Electrical Engineering Department, Tshwane University of Technology, Pretoria, South Africa
Kholopane Pule, Industrial Engineering Department, University of Johannesburg, Johannesburg, South Africa
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To prioritize projects and satisfy both the investors and the society from benefitting from the projects, a mathematical tool which has the characteristics of prediction and evaluation is required. If a dependable forecasting model could be achieved, it will be very valuable for the assessment and selection of projects. This paper employs artificial neural network (ANN) technique in the selection of projects. To demonstrate this technique, the ANN modelis illustrated using Oral, Kettani and Lang’s data on 37 R&D projects for its success. From the validation analysis, it was discovered that artificial neural network displayed a high potential to deciding how projects should be ranked and selected.
Project Selection, Regression Analysis, Artificial Neural Network
To cite this article
Olanrewaju Oludolapo Akanni, Jimoh Abdul-Ganiyu Adisa, Kholopane Pule, Project Selection: Artificial Neural Network Approach, Science Journal of Business and Management. Vol. 1, No. 3, 2013, pp. 37-42. doi: 10.11648/j.sjbm.20130103.11
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