Orthogonal wavelet support vector machine for predicting crude oil prices

Chiroma, Haruna and Abdul-Kareem, Sameem and Abubakar, Adamu and Zeki, Akram M. and Usman, Mohammed Joda (2014) Orthogonal wavelet support vector machine for predicting crude oil prices. In: 1st International Conference on Advanced Data and Information Engineering (DaEng 2013), 16th-18th Dec. 2013, Cititel Hotel, Mid Valley, Kuala Lumpur.

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Abstract

Previous studies mainly used radial basis, sigmoid, polynomial, linear, and hyperbolic functions as the kernel function for computation in the neurons of conventional support vector machine (CSVM) whereas orthogonal wavelet requires less number of iterations to converge than these listed kernel functions. We proposed an orthogonal wavelet support vector machine (OSVM) model for predicting the monthly prices of West Texas Intermediate crude oil prices. For evaluation purposes, we compared the performance of our results with that of the CSVM, and multilayer perceptron neural network (MLPNN). It was found to perform better than the CSVM, and the MLPNN. Moreover, the number of iterations, and time computational complexity of the OSVM model is less than that of CSVM, and MLPNN. Experimental results suggest that the OSVM is effective, robust, and can efficiently be used for crude oil price prediction. Our proposal has the potentials of advancing the prediction accuracy of crude oil prices, which makes it suitable for building intelligent decision support systems.

Item Type:	Proceeding Paper (Slide Presentation)
Additional Information:	6153/36930 (eISBN: 978-981-4585-18-7, ISBN: 978-981-4585-17-0, DOI: 10.1007/978-981-4585-18-7_23)
Uncontrolled Keywords:	support vector machine, orthogonal wavelet, crude oil prices, Kernel function
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:	24 Jun 2014 16:34
Last Modified:	02 May 2024 09:44
URI:	http://irep.iium.edu.my/id/eprint/36930

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