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Economic analysis of risky projects by ANNs

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dc.contributor.authorTaskin, Alev
dc.contributor.authorGuneri, Ali Fuat
dc.contributor.institutionauthorTAŞKIN, Alev
dc.date.accessioned2026-06-27T13:04:36Z
dc.date.issued2006
dc.description.abstractMultilayer 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.en
dc.description.urihttps://doi.org/10.1016/j.amc.2005.07.016
dc.identifier.doi10.1016/j.amc.2005.07.016
dc.identifier.eissn1873-5649
dc.identifier.endpage181
dc.identifier.issn0096-3003
dc.identifier.issue1
dc.identifier.startpage171
dc.identifier.urihttps://hdl.handle.net/20.500.14981/49372
dc.identifier.volume175
dc.identifier.wos000241776800014
dc.language.isoeng
dc.publisherELSEVIER SCIENCE INC
dc.relation.ispartofAPPLIED MATHEMATICS AND COMPUTATION
dc.subjectneural networks
dc.subjectradial basis function
dc.subjectmultilayer perceptron
dc.subjectrisky projects
dc.subjecteconomic analysis
dc.subjectNEURAL-NETWORK
dc.subjectAPPROXIMATION
dc.subjectMathematics
dc.titleEconomic analysis of risky projects by ANNs
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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