Intelligent decision support systems for oil price forecasting

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 predic...

Full description

Bibliographic Details
Main Authors: Chiroma, Haruna, Zavareh, Adeleh Asemi, Baba, Mohd Sapiyan, Ibrahim, Adamu Abubakar, Gital, Abdulsam Ya'u, Zambuk, Fatima Umar
Format: Article
Language:English
English
Published: The Interntaional Journal of Information Science and Management 2015
Subjects:
Online Access:http://irep.iium.edu.my/46196/
http://irep.iium.edu.my/46196/
http://irep.iium.edu.my/46196/1/IJISM.pdf
http://irep.iium.edu.my/46196/4/46196_Intelligent%20decision%20support%20systems%20for%20oil%20price%20forecasting_SCOPUS.pdf
Description
Summary: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.