Modeling and forecasting opec reference basket crude oil prices using artificial neural networks

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dc.contributor.authorMahanthege, SR
dc.contributor.authorChandrasekera, NV
dc.contributor.authorJayasundara, DDM
dc.contributor.editorJayasekara, AGBP
dc.contributor.editorAmarasinghe, YWR
dc.date.accessioned2022-11-17T09:02:58Z
dc.date.available2022-11-17T09:02:58Z
dc.date.issued2016-04
dc.description.abstractWith Organization of petroleum exporting countries (OPEC) being the dominant player in the crude oil industry, it is of great importance to accurately forecast OPEC reference basket (ORB) crude oil prices. This study focuses on forecasting ORB crude oil prices using two Artificial Neural Network (ANN) models: Feedforward Neural Network (FFNN) and Time-Delay Neural Network (TDNN). Training of the networks were done by changing several parameters of the networks. Levenberg-Marquardt training algorithm has been used in training ANN. Results indicates that the TDNN model outperforms the FFNN model in forecasting daily ORB crude oil prices.en_US
dc.identifier.citation****en_US
dc.identifier.conferenceERU Symposium 2016en_US
dc.identifier.departmentEngineering Research Unit, University of Moratuwaen_US
dc.identifier.emails.mahanthege@gmail.comen_US
dc.identifier.emailnvchandrasekara@kln.ac.lken_US
dc.identifier.emailjayasund@kln.ac.lken_US
dc.identifier.facultyEngineeringen_US
dc.identifier.placeMoratuwa, Sri Lankaen_US
dc.identifier.proceedingProceedings of the ERU Symposium 2016en_US
dc.identifier.urihttp://dl.lib.uom.lk/handle/123/19548
dc.identifier.year2016en_US
dc.language.isoenen_US
dc.publisherEngineering Research Unit, Faculty of Engiennring, University of Moratuwaen_US
dc.subjectOPECen_US
dc.subjectCrude oilen_US
dc.subjectFeedforward Neural Networken_US
dc.subjectTime-Delay Neural Networken_US
dc.titleModeling and forecasting opec reference basket crude oil prices using artificial neural networksen_US
dc.typeConference-Abstracten_US

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