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

Nuka Nwiabu, Mirabel Amadi

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.


Keywords


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

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