Building a Decision Support System for Crude Oil Price Prediction using Bayesian Networks

Authors

  • Nuka Nwiabu RIVERS STATE UNIVERSITY PORT HARCOURT, RIVERS STATE, NIGERIA
  • Mirabel Amadi

Keywords:

Bayesian Networks (BNs), Crude oil price, decision support system (DSS)

Abstract

Decision Support Systems are computer based systems that are aimed at assisting decision-makers in taking productive, agile, innovative and reputable decisions. This work presents a Decision Support System using Bayesian Network to predict crude oil price .Bayesian Network technology and its application in predicting crude oil price is presented. Price data obtained from the Central Bank of Nigeria was classed into High and Low cases to denote the upward and downward price movement in which information was revealed. The input data were used in this model to train the network and to validate its generalization ability in other to deliver the best prediction forecast. A linguistic prediction model which utilized the Bayesian Network whose aim was to integrate linguistic information into a quantitative prediction model was established. The results obtained from the linguistic model demonstrate that linguistic information adds value to oil price prediction.

Author Biography

Nuka Nwiabu, RIVERS STATE UNIVERSITY PORT HARCOURT, RIVERS STATE, NIGERIA

Computer Science

References

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Published

2017-12-07

How to Cite

Nwiabu, N., & Amadi, M. (2017). Building a Decision Support System for Crude Oil Price Prediction using Bayesian Networks. American Scientific Research Journal for Engineering, Technology, and Sciences, 38(2), 1–17. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/3556

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Articles