Economic analysis of risky projects by ANNs

Taskin A., Guneri A. F.

APPLIED MATHEMATICS AND COMPUTATION, vol.175, no.1, pp.171-181, 2006 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 175 Issue: 1
  • Publication Date: 2006
  • Doi Number: 10.1016/j.amc.2005.07.016
  • Journal Name: APPLIED MATHEMATICS AND COMPUTATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.171-181
  • Yıldız Technical University Affiliated: No

Abstract

Multilayer perceptron (MLP) and radial basis function (RBF) artificial neural networks (ANN) are used to model economic analysis of risky projects and are presented in this paper. Analytical models of risky projects are investigated and neural network function approximation results are compared. A general, problem independent ANNs are developed for the normalized input values for risky projects. The expected cost value and variance are the outputs of the ANNs. The simulation results of RBF and MLP with respect to a mathematical model are shown and concluded. (c) 2005 Elsevier Inc. All rights reserved.