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...
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| Format: | Proceeding Paper |
| Language: | English English |
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Springer
2014
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| 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 |
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| 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 |