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

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.

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Abstract

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

Item Type:	Conference or Workshop Item (Invited Papers)
Additional Information:	7132/40164 Proceedings of the Fourth INNS Symposia Series on Computational Intelligence in Information Systems (INNS-CIIS 2014)ISBN 978-3-319-13152-8 -pp 21-30
Uncontrolled Keywords:	Propane Spot Rice, CRT, RVFLN, SVM, Estimation
Subjects:	Q Science > Q Science (General) > Q300 Cybernetics > Q350 Information theory
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:	Dr Adamu Abubakar
Date Deposited:	24 Dec 2014 16:06
Last Modified:	19 Sep 2017 18:40
URI:	http://irep.iium.edu.my/id/eprint/40164

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