Intelligent Decision Support Systems for Oil Price Forecasting

Intelligent Decision Support Systems for Oil Price Forecasting

<p>This research studies the application of hybrid algorithms for predicting the prices of crude oil. Brent crude oil price data and hybrid intelligent algorithm (time delay neural network, probabilistic neural network, and fuzzy logic) were used to build intelligent decision support systems f...

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Main Authors: Haruna Chiroma, Adeleh Asemi Zavareh, Mohd Sapiyan Baba, Adamu I. Abubakar, Abdulsalam Ya’u Gital, Fatima Umar Zambuk
Format: Article
Language:English
Published: Regional Information Center for Science and Technology (RICeST) 2015-11-01
Series:International Journal of Information Science and Management
Online Access:https://ijism.ricest.ac.ir/index.php/ijism/article/view/671
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spelling doaj-84012d63c9314adda328c9ef031d882b2020-11-25T03:10:59ZengRegional Information Center for Science and Technology (RICeST)International Journal of Information Science and Management 2008-83022008-83102015-11-0100242Intelligent Decision Support Systems for Oil Price ForecastingHaruna Chiroma0Adeleh Asemi Zavareh1Mohd Sapiyan Baba2Adamu I. Abubakar3Abdulsalam Ya’u Gital4Fatima Umar Zambuk5Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, MalaysiaFaculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, MalaysiaFaculty of Computer Science, Gulf University of Science and Technology, KuwaitFaculty of Information and Communication Technology, International Islamic University Kuala Lumpur, MalaysiaMathematics Program, School of Science, Abubakar Tafawa Balewa University, Bauchi, NigeriaMathematics Program, School of Science, Abubakar Tafawa Balewa University, Bauchi, Nigeria<p>This research studies the application of hybrid algorithms for predicting the prices of crude oil. Brent crude oil price data and hybrid intelligent algorithm (time delay neural network, probabilistic neural network, and fuzzy logic) were used to build intelligent decision support systems for predicting crude oil prices. The proposed model was able to predict future crude oil prices from August 2013 to July 2014. Future prices can guide decision makers in economic planning and taking effective measures to tackle the negative impact of crude oil price volatility. Energy demand and supply projection can effectively be tackled with accurate forecasts of crude oil prices, which in turn can create stability in the oil market. The future crude oil prices predict by the intelligent decision support systems can be used by both government and international organizations related to crude oil such as organization of petroleum exporting countries (OPEC) for policy formulation in the next one year.  </p><p>DOR: <span>98.1000/1726-8125.2015.0.47.0.0.73.103</span></p>https://ijism.ricest.ac.ir/index.php/ijism/article/view/671
collection DOAJ
language English
format Article
sources DOAJ
author Haruna Chiroma
Adeleh Asemi Zavareh
Mohd Sapiyan Baba
Adamu I. Abubakar
Abdulsalam Ya’u Gital
Fatima Umar Zambuk
spellingShingle Haruna Chiroma
Adeleh Asemi Zavareh
Mohd Sapiyan Baba
Adamu I. Abubakar
Abdulsalam Ya’u Gital
Fatima Umar Zambuk
Intelligent Decision Support Systems for Oil Price Forecasting
International Journal of Information Science and Management
author_facet Haruna Chiroma
Adeleh Asemi Zavareh
Mohd Sapiyan Baba
Adamu I. Abubakar
Abdulsalam Ya’u Gital
Fatima Umar Zambuk
author_sort Haruna Chiroma
title Intelligent Decision Support Systems for Oil Price Forecasting
title_short Intelligent Decision Support Systems for Oil Price Forecasting
title_full Intelligent Decision Support Systems for Oil Price Forecasting
title_fullStr Intelligent Decision Support Systems for Oil Price Forecasting
title_full_unstemmed Intelligent Decision Support Systems for Oil Price Forecasting
title_sort intelligent decision support systems for oil price forecasting
publisher Regional Information Center for Science and Technology (RICeST)
series International Journal of Information Science and Management
issn 2008-8302
2008-8310
publishDate 2015-11-01
description <p>This research studies the application of hybrid algorithms for predicting the prices of crude oil. Brent crude oil price data and hybrid intelligent algorithm (time delay neural network, probabilistic neural network, and fuzzy logic) were used to build intelligent decision support systems for predicting crude oil prices. The proposed model was able to predict future crude oil prices from August 2013 to July 2014. Future prices can guide decision makers in economic planning and taking effective measures to tackle the negative impact of crude oil price volatility. Energy demand and supply projection can effectively be tackled with accurate forecasts of crude oil prices, which in turn can create stability in the oil market. The future crude oil prices predict by the intelligent decision support systems can be used by both government and international organizations related to crude oil such as organization of petroleum exporting countries (OPEC) for policy formulation in the next one year.  </p><p>DOR: <span>98.1000/1726-8125.2015.0.47.0.0.73.103</span></p>
url https://ijism.ricest.ac.ir/index.php/ijism/article/view/671
work_keys_str_mv AT harunachiroma intelligentdecisionsupportsystemsforoilpriceforecasting
AT adelehasemizavareh intelligentdecisionsupportsystemsforoilpriceforecasting
AT mohdsapiyanbaba intelligentdecisionsupportsystemsforoilpriceforecasting
AT adamuiabubakar intelligentdecisionsupportsystemsforoilpriceforecasting
AT abdulsalamyaugital intelligentdecisionsupportsystemsforoilpriceforecasting
AT fatimaumarzambuk intelligentdecisionsupportsystemsforoilpriceforecasting
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