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文章基本信息

  • 标题:Intelligent Decision Support Systems for Oil Price Forecasting
  • 本地全文:下载
  • 作者:Haruna Chiroma ; Adeleh Asemi Zavareh ; Mohd Sapiyan Baba
  • 期刊名称:International Journal of Information Science and Management (IJISM)
  • 印刷版ISSN:2008-8302
  • 电子版ISSN:2008-8310
  • 出版年度:2015
  • 语种:English
  • 出版社:REGIONAL INFORMATION CENTER FOR SCIENCE AND TECHNOLOGY
  • 其他摘要: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. DOR: 98.1000/1726-8125.2015.0.47.0.0.73.103
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