Proceedings of the 2007 Summer Computer Simulation Conference

Nasr, George E.; Dibeh, Ghassan; Achkar, Antoine

dc.contributor.editor	Wainer, Gabriel A.
dc.contributor.editor	Vakilzadian, Hamid
dc.coverage.spatial	Marriot Mission Valley, San Diego, California	en_US
dc.creator	Nasr, George E.	en_US
dc.creator	Dibeh, Ghassan	en_US
dc.creator	Achkar, Antoine	en_US
dc.date.accessioned	2017-08-25T09:51:23Z
dc.date.available	2017-08-25T09:51:23Z
dc.date.datecopyrighted	2007	en_US
dc.identifier.isbn	1565553160	en_US
dc.identifier.uri	http://hdl.handle.net/10725/6084
dc.description.abstract	A feedforward neural network model is used to forecast turning points in the business cycle of postwar Lebanon. The NN has as inputs seven indicators of economic activity and as output the probability of a recession. The three-layered network is estimated using the back propagation algorithm. The NN is then used to forecast recursively a half-year ahead the probability of a recession in that period. The NN shows that two of the economic indicators can be used to construct a composite index of leading indicators that can be used to predict business cycles in the future.	en_US
dc.description.sponsorship	Society for Modeling and Simulation International (SCS)	en_US
dc.language.iso	en	en_US
dc.publisher	Society For Computer Simulation	en_US
dc.relation.ispartofseries	Simulation series ; v. 39, no. 4
dc.subject	Computer simulation -- Congresses	en_US
dc.title	Proceedings of the 2007 Summer Computer Simulation Conference	en_US
dc.title	Predicting business cycle turning points with neural networks in an information-poor economy	en_US
dc.type	Conference Paper / Proceeding	en_US
dc.creator.school	SOB	en_US
dc.creator.school	SOE
dc.creator.identifier	199390170	en_US
dc.creator.identifier	199490150	en_US
dc.creator.department	Department of Economics (ECON)	en_US
dc.description.embargo	N/A	en_US
dc.description.physdesc	1261, [57] p.: ill.	en_US
dc.title.altrnative	2007 Summer Computer Simulation Conference	en_US
dc.title.altrnative	SCSC '07	en_US
dc.publisher.place	San Diego, Calif.	en_US
dc.keywords	Neural Networks	en_US
dc.keywords	Forecasting	en_US
dc.keywords	Business Cycles	en_US
dc.description.bibliographiccitations	Includes bibliographical references.	en_US
dc.identifier.ctation	Nasr, G. E., Dibeh, G., & Achkar, A. (2007, July). Predicting business cycle turning points with neural networks in an information-poor economy. In Proceedings of the 2007 Summer Computer Simulation Conference (pp. 627-631). San diego, CA.: Society for Computer Simulation International.	en_US
dc.creator.email	genasr@lau.edu.lb	en_US
dc.creator.email	gdibeh@lau.edu.lb	en_US
dc.date.created	July 15-18, 2007	en_US
dc.description.pages	627-631	en_US
dc.conference.subtitle	SCSC '07 : the, July 15-18, 2007	en_US
dc.description.tou	http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php	en_US
dc.identifier.url	http://dl.acm.org/citation.cfm?id=1358008	en_US
dc.date.datepublished	2007	en_US
dc.creator.ispartof	Lebanese American University	en_US