Orthogonal wavelet support vector machine for predicting crude oil prices

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 func...

Full description

Bibliographic Details
Main Authors: Chiroma, Haruna, Abdul-Kareem, Sameem, Abubakar, Adamu, Zeki, Akram M., Usman, Mohammed Joda
Format: Proceeding Paper
Language:English
English
Published: Springer 2014
Subjects:
Online Access:http://irep.iium.edu.my/36930/
http://irep.iium.edu.my/36930/4/Orthogonal_Wavelet_Support_Vector_Machine_for_Predicting_Crude_Oil_Prices%2B.pdf
http://irep.iium.edu.my/36930/7/36930_Orthogonal%20wavelet%20support%20vector%20machine%20for%20predicting%20crude%20oil%20prices.SCOPUS.pdf
_version_ 1848781322399514624
author Chiroma, Haruna
Abdul-Kareem, Sameem
Abubakar, Adamu
Zeki, Akram M.
Usman, Mohammed Joda
author_facet Chiroma, Haruna
Abdul-Kareem, Sameem
Abubakar, Adamu
Zeki, Akram M.
Usman, Mohammed Joda
author_sort Chiroma, Haruna
building IIUM Repository
collection Online Access
description 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.
first_indexed 2025-11-14T15:47:43Z
format Proceeding Paper
id iium-36930
institution International Islamic University Malaysia
institution_category Local University
language English
English
last_indexed 2025-11-14T15:47:43Z
publishDate 2014
publisher Springer
recordtype eprints
repository_type Digital Repository
spelling iium-369302024-05-02T01:44:43Z http://irep.iium.edu.my/36930/ Orthogonal wavelet support vector machine for predicting crude oil prices Chiroma, Haruna Abdul-Kareem, Sameem Abubakar, Adamu Zeki, Akram M. Usman, Mohammed Joda T Technology (General) 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. Springer 2014 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/36930/4/Orthogonal_Wavelet_Support_Vector_Machine_for_Predicting_Crude_Oil_Prices%2B.pdf application/pdf en http://irep.iium.edu.my/36930/7/36930_Orthogonal%20wavelet%20support%20vector%20machine%20for%20predicting%20crude%20oil%20prices.SCOPUS.pdf 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. http://link.springer.com/chapter/10.1007%2F978-981-4585-18-7_23 doi:10.1007/978-981-4585-18-7_23
spellingShingle T Technology (General)
Chiroma, Haruna
Abdul-Kareem, Sameem
Abubakar, Adamu
Zeki, Akram M.
Usman, Mohammed Joda
Orthogonal wavelet support vector machine for predicting crude oil prices
title Orthogonal wavelet support vector machine for predicting crude oil prices
title_full Orthogonal wavelet support vector machine for predicting crude oil prices
title_fullStr Orthogonal wavelet support vector machine for predicting crude oil prices
title_full_unstemmed Orthogonal wavelet support vector machine for predicting crude oil prices
title_short Orthogonal wavelet support vector machine for predicting crude oil prices
title_sort orthogonal wavelet support vector machine for predicting crude oil prices
topic T Technology (General)
url http://irep.iium.edu.my/36930/
http://irep.iium.edu.my/36930/
http://irep.iium.edu.my/36930/
http://irep.iium.edu.my/36930/4/Orthogonal_Wavelet_Support_Vector_Machine_for_Predicting_Crude_Oil_Prices%2B.pdf
http://irep.iium.edu.my/36930/7/36930_Orthogonal%20wavelet%20support%20vector%20machine%20for%20predicting%20crude%20oil%20prices.SCOPUS.pdf