Understanding the social and economic factors affecting adverse events in an active theater of war: A neural network approach

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dc.contributor.authorÇakıt, Erman
dc.contributor.authorKarwowski, Waldemar
dc.contributor.editorHoffman, M
dc.date.accessioned13.07.201910:50:10
dc.date.accessioned2019-07-16T09:17:22Z
dc.date.available13.07.201910:50:10
dc.date.available2019-07-16T09:17:22Z
dc.date.issued2018
dc.departmentMühendislik Fakültesi
dc.descriptionAHFE International Conference on Cross-Cultural Decision Making (CCDM) -- JUL 17-21, 2017 -- Los Angeles, CA
dc.descriptionWOS:000451449700020
dc.description.abstractThis study focused on the application of artificial neural networks (ANNs) to model the effect of infrastructure development projects on terrorism security events in Afghanistan. The dataset include adverse events and infrastructure aid activity in Afghanistan from 2001 to 2010. Several ANN models were generated and investigated for Afghanistan and its seven regions. In addition to a soft-computing approach, a multiple linear regression (MLR) analysis was also performed to evaluate whether or not the ANN approach showed superior predictive performance compared to a classical statistical approach. According to the performance comparison, the developed ANN model provided better prediction accuracy with respect to the MLR approach. The results obtained from this analysis demonstrate that ANNs can predict the occurrence of adverse events according to economic infrastructure aid activity data.
dc.description.sponsorshipOffice of Naval Research (ONR) [1052339]
dc.description.sponsorshipThe authors are grateful for the support of the Office of Naval Research (ONR) under Grant No. 1052339, Complex Systems Engineering for Rapid Computational Socio-Cultural Network Analysis, and the helpful guidance of ONR Program Management and the technical team.
dc.identifier.doi10.1007/978-3-319-60747-4_20
dc.identifier.endpage223en_US
dc.identifier.isbn978-3-319-60747-4; 978-3-319-60746-7
dc.identifier.issn2194-5357
dc.identifier.issn2194-5365
dc.identifier.scopusqualityN/A
dc.identifier.startpage215en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-319-60747-4_20
dc.identifier.urihttps://hdl.handle.net/20.500.12451/4740
dc.identifier.volume610en_US
dc.identifier.wosWOS:000451449700020
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofAdvances in Cross-Cultural Decision Making , (AHFE 2017)
dc.relation.ispartofseriesAdvances in Intelligent Systems and Computing
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectInfrastructure Aid Activity
dc.subjectAdverse Events
dc.subjectArtificial Neural Networks
dc.subjectMultiple Linear Regression
dc.titleUnderstanding the social and economic factors affecting adverse events in an active theater of war: A neural network approach
dc.typeConference Object

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