Co - active neuro-fuzzy inference systems model for predicting crude oil price based on OECD inventories

Chiroma, Haruna and Abdulkareem, Sameem and Abubakar, Adamu and Zeki, Akram M. and Gital, Abdulsam Ya'u and Usman, Mohammed Joda (2013) Co - active neuro-fuzzy inference systems model for predicting crude oil price based on OECD inventories. In: 3rd International Conference on Research and Innovation in Information Systems – 2013 (ICRIIS’13), 27 -28th November 2013, Uniten, Kajang.

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Abstract

This paper present a novel approach to crude oil price prediction based on co-active neuro-fuzzy inference systems (CANFIS) instead of the commonly use fuzzy neural network and adaptive network-based fuzzy inference systems due to superiority and robustness of the CANFIS model. Monthly data of West Texas Intermediate crude oil price and organization for economic co-operation and development (OECD) inventories, obtained from US Department of Energy were used to built the propose model. The CANFIS prediction model was trained, validated and tested. The performance of our approach is measured using mean square error, root mean square error, mean absolute error and regression. Suggestion from the results shows that the CANFIS demonstrated a high level of generalization capability with relatively very low error and high correlation which exhibited successful prediction performance of the proposal. The model has the potential of being developed into real life systems for use by both government and private businesses for making strategic planning that can boost economic activities.

Item Type:	Conference or Workshop Item (Full Paper)
Additional Information:	6153/35755
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User:	Akram M Zeki
Date Deposited:	20 Feb 2014 16:17
Last Modified:	08 Dec 2014 11:47
URI:	http://irep.iium.edu.my/id/eprint/35755

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