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

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dc.contributor.author Mahanthege, SR
dc.contributor.author Chandrasekera, NV
dc.contributor.author Jayasundara, DDM
dc.contributor.editor Jayasekara, AGBP
dc.contributor.editor Amarasinghe, YWR
dc.date.accessioned 2022-11-17T09:02:58Z
dc.date.available 2022-11-17T09:02:58Z
dc.date.issued 2016-04
dc.identifier.citation **** en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/19548
dc.description.abstract With 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.language.iso en en_US
dc.publisher Engineering Research Unit, Faculty of Engiennring, University of Moratuwa en_US
dc.subject OPEC en_US
dc.subject Crude oil en_US
dc.subject Feedforward Neural Network en_US
dc.subject Time-Delay Neural Network en_US
dc.title Modeling and forecasting opec reference basket crude oil prices using artificial neural networks en_US
dc.type Conference-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Engineering Research Unit, University of Moratuwa en_US
dc.identifier.year 2016 en_US
dc.identifier.conference ERU Symposium 2016 en_US
dc.identifier.place Moratuwa, Sri Lanka en_US
dc.identifier.proceeding Proceedings of the ERU Symposium 2016 en_US
dc.identifier.email s.mahanthege@gmail.com en_US
dc.identifier.email nvchandrasekara@kln.ac.lk en_US
dc.identifier.email jayasund@kln.ac.lk en_US


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