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An Intelligent Modeling of Oil Consumption

Chiroma, Haruna and Abdulkareem, Sameem and Muaz, Sanah Abdullahi and Abubakar, Adamu I. and Sutoyo, Edi and Mungad , Mungad and Saadi, Younes and Sari, Eka Novita and Tutut, Herawan (2015) An Intelligent Modeling of Oil Consumption. In: Advances in Intelligent Informatics. Advances in Intelligent Systems and Computing, 320 . Springer International Publishing, Switzerland, pp. 557-568. ISBN 978-3-319-11217-6 (print); 978-3-319-11218-3 (online)

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Abstract

In this study, we select Middle East countries involving Jordan, Lebanon, Oman, and Saudi Arabia for modeling oil consumption based on computational intelligence methods. The limitations associated with Levenberg-Marquardt (LM) Neural Network (NN) motivated this research to optimize the parameters of NN through Artificial Bee Colony Algorithm (ABC-LM) to build a model for the prediction of oil consumption. The proposed model was competent to predict oil consumption with improved accuracy and convergence speed. The ABC-LM performs better than the standard LMNN, Genetically optimized NN, and Back-propagation NN. The proposed model may guide policy makers in the formulation of domestic and international policies related to oil consumption and economic development. The approach presented in the study can easily be implemented into a software for use by the government of Jordan, Lebanon, Oman, and Saudi Arabia.

Item Type: Book Section
Uncontrolled Keywords: Artificial Bee Colony; Neural Network; Levenberg-Marquardt; Oil Consumption; Prediction
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 14 Jun 2016 06:14
Last Modified: 14 Jun 2016 06:14
URI: http://umpir.ump.edu.my/id/eprint/8251
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