Estimation of Middle-East oil consumption using hybrid meta-heuristic algorithms

The consumption of energy has significantly increased in theworld during the preceding decade. Two-third of energy requirements are produced by oil and gas. Estimation of oil consumption can give clues on the future energy consumption. In this study, the effectiveness of three hybrid metaheuristi...

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Main Authors:	Haruna, Chiroma, Khan, Abdullah, Abubakar, Adamu, Saadi, Younes, Abdullahi Muaz, Sanah, Ya’u Gital, Abdulsalam, Shuib, Liyana
Format:	Book Chapter
Language:	English English
Published:	Springer Nature Singapore 2019
Subjects:	Q350 Information theory
Online Access:	http://irep.iium.edu.my/74274/ http://irep.iium.edu.my/74274/ http://irep.iium.edu.my/74274/ http://irep.iium.edu.my/74274/7/74294_Hybrid%20of%20Swarm%20Intelligent%20Algorithms%20in%20Medical%20Applications_Scopus.pdf http://irep.iium.edu.my/74274/13/74274_Estimation%20of%20Middle-East%20oil%20consumption.pdf

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recordtype	eprints
spelling	iium-742742020-01-31T03:36:37Z http://irep.iium.edu.my/74274/ Estimation of Middle-East oil consumption using hybrid meta-heuristic algorithms Haruna, Chiroma Khan, Abdullah Abubakar, Adamu Saadi, Younes Abdullahi Muaz, Sanah Ya’u Gital, Abdulsalam Shuib, Liyana Q350 Information theory The consumption of energy has significantly increased in theworld during the preceding decade. Two-third of energy requirements are produced by oil and gas. Estimation of oil consumption can give clues on the future energy consumption. In this study, the effectiveness of three hybrid metaheuristic algorithms, namely, Cuckoo Search Neural Network (CSNN), Artificial Bee Colony Neural Network (ABCNN), and Genetic Algorithm Neural Network (GANN) were investigated for the estimation of oil consumption. The simulation results showed that the CSNN improved the estimation accuracy of oil consumption over ABCNN and GANN whereas GANN improved convergence speed over CSNN and ABCNN. The study has shown that in terms of accuracy, the CSNN is appropriate for the estimation of oil consumption. In terms of convergence speed, GANN is the most suitable algorithms Springer Nature Singapore 2019 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/74274/7/74294_Hybrid%20of%20Swarm%20Intelligent%20Algorithms%20in%20Medical%20Applications_Scopus.pdf application/pdf en http://irep.iium.edu.my/74274/13/74274_Estimation%20of%20Middle-East%20oil%20consumption.pdf Haruna, Chiroma and Khan, Abdullah and Abubakar, Adamu and Saadi, Younes and Abdullahi Muaz, Sanah and Ya’u Gital, Abdulsalam and Shuib, Liyana (2019) Estimation of Middle-East oil consumption using hybrid meta-heuristic algorithms. In: Lecture Notes in Electrical Engineering. Springer Nature Singapore, Singapore, pp. 139-150. ISBN 978-981-13-1797-2 https://link.springer.com/chapter/10.1007%2F978-981-13-1799-6_16 https://doi.org/10.1007/978-981-13-1799-6
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	Q350 Information theory
spellingShingle	Q350 Information theory Haruna, Chiroma Khan, Abdullah Abubakar, Adamu Saadi, Younes Abdullahi Muaz, Sanah Ya’u Gital, Abdulsalam Shuib, Liyana Estimation of Middle-East oil consumption using hybrid meta-heuristic algorithms
description	The consumption of energy has significantly increased in theworld during the preceding decade. Two-third of energy requirements are produced by oil and gas. Estimation of oil consumption can give clues on the future energy consumption. In this study, the effectiveness of three hybrid metaheuristic algorithms, namely, Cuckoo Search Neural Network (CSNN), Artificial Bee Colony Neural Network (ABCNN), and Genetic Algorithm Neural Network (GANN) were investigated for the estimation of oil consumption. The simulation results showed that the CSNN improved the estimation accuracy of oil consumption over ABCNN and GANN whereas GANN improved convergence speed over CSNN and ABCNN. The study has shown that in terms of accuracy, the CSNN is appropriate for the estimation of oil consumption. In terms of convergence speed, GANN is the most suitable algorithms
format	Book Chapter
author	Haruna, Chiroma Khan, Abdullah Abubakar, Adamu Saadi, Younes Abdullahi Muaz, Sanah Ya’u Gital, Abdulsalam Shuib, Liyana
author_facet	Haruna, Chiroma Khan, Abdullah Abubakar, Adamu Saadi, Younes Abdullahi Muaz, Sanah Ya’u Gital, Abdulsalam Shuib, Liyana
author_sort	Haruna, Chiroma
title	Estimation of Middle-East oil consumption using hybrid meta-heuristic algorithms
title_short	Estimation of Middle-East oil consumption using hybrid meta-heuristic algorithms
title_full	Estimation of Middle-East oil consumption using hybrid meta-heuristic algorithms
title_fullStr	Estimation of Middle-East oil consumption using hybrid meta-heuristic algorithms
title_full_unstemmed	Estimation of Middle-East oil consumption using hybrid meta-heuristic algorithms
title_sort	estimation of middle-east oil consumption using hybrid meta-heuristic algorithms
publisher	Springer Nature Singapore
publishDate	2019
url	http://irep.iium.edu.my/74274/ http://irep.iium.edu.my/74274/ http://irep.iium.edu.my/74274/ http://irep.iium.edu.my/74274/7/74294_Hybrid%20of%20Swarm%20Intelligent%20Algorithms%20in%20Medical%20Applications_Scopus.pdf http://irep.iium.edu.my/74274/13/74274_Estimation%20of%20Middle-East%20oil%20consumption.pdf
first_indexed	2023-09-18T21:45:13Z
last_indexed	2023-09-18T21:45:13Z
_version_	1777413404113240064

Estimation of Middle-East oil consumption using hybrid meta-heuristic algorithms

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