An ensemble CRT, RVFLN, SVM method for estimating Propane Spot Price

In this paper, we propose an ensemble of the CRT-RVFLN-SVM (Classification and Regression Tree (CRT), Random Variable Functional Link Neural Network (RVFLN), and Support Vector Machine (SVM)) to improve robustness and effectiveness in estimating propane spot price. The propane spot price data which...

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Main Authors: Haruna, Chiroma, Sameem, Abdul-kareem, Abdulsalam, Gital, Sanah, Abdullahi Muaz, Adamu, Abubakar Ibrahim, Mungad, Mu, Tutut, Herawan
Format: Proceeding Paper
Language:English
English
English
English
Published: 2015
Subjects:
Online Access:http://irep.iium.edu.my/40164/
http://irep.iium.edu.my/40164/1/18_-An_Ensemble_CRT%2C_RVFLN%2C_SVM_Method_for_Estimating_Propane_Spot_Price.pdf
http://irep.iium.edu.my/40164/4/bfm_978-3-319-13153-5_1_Adamu.pdf
http://irep.iium.edu.my/40164/7/Adamu_front_pg.pdf
http://irep.iium.edu.my/40164/9/40164_An%20ensemble%20CRT%2C%20RVFLN%2C%20SVM%20method_Scopus.pdf
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author Haruna, Chiroma
Sameem, Abdul-kareem
Abdulsalam, Gital
Sanah, Abdullahi Muaz
Adamu, Abubakar Ibrahim
Mungad, Mu
Tutut, Herawan
author_facet Haruna, Chiroma
Sameem, Abdul-kareem
Abdulsalam, Gital
Sanah, Abdullahi Muaz
Adamu, Abubakar Ibrahim
Mungad, Mu
Tutut, Herawan
author_sort Haruna, Chiroma
building IIUM Repository
collection Online Access
description In this paper, we propose an ensemble of the CRT-RVFLN-SVM (Classification and Regression Tree (CRT), Random Variable Functional Link Neural Network (RVFLN), and Support Vector Machine (SVM)) to improve robustness and effectiveness in estimating propane spot price. The propane spot price data which are collected from the Energy Information Administration of the US Department of Energy and Barchart were used to build an ensemble CRT-RVFLN-SVM model for the estimating of propane spot price. For the purpose of evaluation, the constituted intelligent computing technologies of the proposed ensemble methodology in addition to Multilayer Back-Propagation Neural Network (MBPNN) were also applied to estimate the propane spot price. Experimental results show that the proposed ensemble CRT-RVFLN-SVM model has improved the performance of CRT, RVFLN, SVM, and MBPNN. The can help to reduce the level of future uncertainty of the propane spot price. Propane investors can use our model as an alternative investment tool for generating more revenue because accurate estimations of future propane price implies generating more profits
first_indexed 2025-11-14T15:56:58Z
format Proceeding Paper
id iium-40164
institution International Islamic University Malaysia
institution_category Local University
language English
English
English
English
last_indexed 2025-11-14T15:56:58Z
publishDate 2015
recordtype eprints
repository_type Digital Repository
spelling iium-401642017-09-19T10:40:02Z http://irep.iium.edu.my/40164/ An ensemble CRT, RVFLN, SVM method for estimating Propane Spot Price Haruna, Chiroma Sameem, Abdul-kareem Abdulsalam, Gital Sanah, Abdullahi Muaz Adamu, Abubakar Ibrahim Mungad, Mu Tutut, Herawan Q350 Information theory In this paper, we propose an ensemble of the CRT-RVFLN-SVM (Classification and Regression Tree (CRT), Random Variable Functional Link Neural Network (RVFLN), and Support Vector Machine (SVM)) to improve robustness and effectiveness in estimating propane spot price. The propane spot price data which are collected from the Energy Information Administration of the US Department of Energy and Barchart were used to build an ensemble CRT-RVFLN-SVM model for the estimating of propane spot price. For the purpose of evaluation, the constituted intelligent computing technologies of the proposed ensemble methodology in addition to Multilayer Back-Propagation Neural Network (MBPNN) were also applied to estimate the propane spot price. Experimental results show that the proposed ensemble CRT-RVFLN-SVM model has improved the performance of CRT, RVFLN, SVM, and MBPNN. The can help to reduce the level of future uncertainty of the propane spot price. Propane investors can use our model as an alternative investment tool for generating more revenue because accurate estimations of future propane price implies generating more profits 2015 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/40164/1/18_-An_Ensemble_CRT%2C_RVFLN%2C_SVM_Method_for_Estimating_Propane_Spot_Price.pdf application/pdf en http://irep.iium.edu.my/40164/4/bfm_978-3-319-13153-5_1_Adamu.pdf application/pdf en http://irep.iium.edu.my/40164/7/Adamu_front_pg.pdf application/pdf en http://irep.iium.edu.my/40164/9/40164_An%20ensemble%20CRT%2C%20RVFLN%2C%20SVM%20method_Scopus.pdf Haruna, Chiroma and Sameem, Abdul-kareem and Abdulsalam, Gital and Sanah, Abdullahi Muaz and Adamu, Abubakar Ibrahim and Mungad, Mu and Tutut, Herawan (2015) An ensemble CRT, RVFLN, SVM method for estimating Propane Spot Price. In: Fourth INNS Symposia Series on Computational Intelligence in Information Systems (INNS-CIIS 2014), 7-9 November 2014, Brunei. http://link.springer.com/chapter/10.1007%2F978-3-319-13153-5_3#page-1
spellingShingle Q350 Information theory
Haruna, Chiroma
Sameem, Abdul-kareem
Abdulsalam, Gital
Sanah, Abdullahi Muaz
Adamu, Abubakar Ibrahim
Mungad, Mu
Tutut, Herawan
An ensemble CRT, RVFLN, SVM method for estimating Propane Spot Price
title An ensemble CRT, RVFLN, SVM method for estimating Propane Spot Price
title_full An ensemble CRT, RVFLN, SVM method for estimating Propane Spot Price
title_fullStr An ensemble CRT, RVFLN, SVM method for estimating Propane Spot Price
title_full_unstemmed An ensemble CRT, RVFLN, SVM method for estimating Propane Spot Price
title_short An ensemble CRT, RVFLN, SVM method for estimating Propane Spot Price
title_sort ensemble crt, rvfln, svm method for estimating propane spot price
topic Q350 Information theory
url http://irep.iium.edu.my/40164/
http://irep.iium.edu.my/40164/
http://irep.iium.edu.my/40164/1/18_-An_Ensemble_CRT%2C_RVFLN%2C_SVM_Method_for_Estimating_Propane_Spot_Price.pdf
http://irep.iium.edu.my/40164/4/bfm_978-3-319-13153-5_1_Adamu.pdf
http://irep.iium.edu.my/40164/7/Adamu_front_pg.pdf
http://irep.iium.edu.my/40164/9/40164_An%20ensemble%20CRT%2C%20RVFLN%2C%20SVM%20method_Scopus.pdf