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A reliability based consistent fuzzy preference relations – fuzzy similarity for risk assessment in oil and gas industry

In decision making, linguistic variables tend to be complex to handle but they make more sense than classical fuzzy numbers. Fuzziness is not sufficient enough to deal with information and degree of reliability of information is critical. Znumbers is proposed to model the uncertainty produced by hum...

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Main Authors:	Ku Muhammad Naim, Ku Khalif, Adam Shariff Adli, Aminuddin, Ahmad Syafadhli, Abu Bakar, Noor Zuraidin, Mohd Safar, Alexander, Gegov
Format:	Conference or Workshop Item
Language:	English English
Published:	2019
Subjects:	QA76 Computer software TP Chemical technology
Online Access:	http://umpir.ump.edu.my/id/eprint/26489/1/78.%20A%20reliability%20based%20consistent%20fuzzy%20preference%20relations.pdf http://umpir.ump.edu.my/id/eprint/26489/2/78.1%20A%20reliability%20based%20consistent%20fuzzy%20preference%20relations.pdf http://umpir.ump.edu.my/id/eprint/26489/
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id	my.ump.umpir.26489
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spelling	my.ump.umpir.264892019-12-23T07:44:32Z http://umpir.ump.edu.my/id/eprint/26489/ A reliability based consistent fuzzy preference relations – fuzzy similarity for risk assessment in oil and gas industry Ku Muhammad Naim, Ku Khalif Adam Shariff Adli, Aminuddin Ahmad Syafadhli, Abu Bakar Noor Zuraidin, Mohd Safar Alexander, Gegov QA76 Computer software TP Chemical technology In decision making, linguistic variables tend to be complex to handle but they make more sense than classical fuzzy numbers. Fuzziness is not sufficient enough to deal with information and degree of reliability of information is critical. Znumbers is proposed to model the uncertainty produced by human judgment when eliciting information. Therefore, the implementation of z-numbers is taken into consideration, where it has more authority to describe the knowledge of human being and extensively used in the uncertain information development. This issue has motivated the authors to propose fuzzy multi criteria group decision making methodology using z-numbers. The proposed methodology is demonstrated the capability to handle knowledge of human being and uncertain information for risk assessment in oil and gas industry. This assessment is due to periodic basis, which will give insights from the operational until the strategic level of decision making process that is capable of dealing with uncertainty in human judgment. The consistent fuzzy preference relations is developed to calculate the preference-weights of the criteria related based on the derived network structure. The fuzzy similarity measure method is applied to resolve conflicts arising from differences in information and opinions provided by the decision makers. The proposed methodology is constructed without losing the generality of the consistent fuzzy preference relations and fuzzy similarity under fuzzy environment 2019 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26489/1/78.%20A%20reliability%20based%20consistent%20fuzzy%20preference%20relations.pdf pdf en http://umpir.ump.edu.my/id/eprint/26489/2/78.1%20A%20reliability%20based%20consistent%20fuzzy%20preference%20relations.pdf Ku Muhammad Naim, Ku Khalif and Adam Shariff Adli, Aminuddin and Ahmad Syafadhli, Abu Bakar and Noor Zuraidin, Mohd Safar and Alexander, Gegov (2019) A reliability based consistent fuzzy preference relations – fuzzy similarity for risk assessment in oil and gas industry. In: The Ninth International Conference on Geotechnique, Construction Materials and Environment (GEOMATE 2019), 20-22 November 2019 , Tokyo, Japan. pp. 1-6.. ISBN 978-4-909106025 C3051
institution	Universiti Malaysia Pahang
building	UMP Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Pahang
content_source	UMP Institutional Repository
url_provider	http://umpir.ump.edu.my/
language	English English
topic	QA76 Computer software TP Chemical technology
spellingShingle	QA76 Computer software TP Chemical technology Ku Muhammad Naim, Ku Khalif Adam Shariff Adli, Aminuddin Ahmad Syafadhli, Abu Bakar Noor Zuraidin, Mohd Safar Alexander, Gegov A reliability based consistent fuzzy preference relations – fuzzy similarity for risk assessment in oil and gas industry
description	In decision making, linguistic variables tend to be complex to handle but they make more sense than classical fuzzy numbers. Fuzziness is not sufficient enough to deal with information and degree of reliability of information is critical. Znumbers is proposed to model the uncertainty produced by human judgment when eliciting information. Therefore, the implementation of z-numbers is taken into consideration, where it has more authority to describe the knowledge of human being and extensively used in the uncertain information development. This issue has motivated the authors to propose fuzzy multi criteria group decision making methodology using z-numbers. The proposed methodology is demonstrated the capability to handle knowledge of human being and uncertain information for risk assessment in oil and gas industry. This assessment is due to periodic basis, which will give insights from the operational until the strategic level of decision making process that is capable of dealing with uncertainty in human judgment. The consistent fuzzy preference relations is developed to calculate the preference-weights of the criteria related based on the derived network structure. The fuzzy similarity measure method is applied to resolve conflicts arising from differences in information and opinions provided by the decision makers. The proposed methodology is constructed without losing the generality of the consistent fuzzy preference relations and fuzzy similarity under fuzzy environment
format	Conference or Workshop Item
author	Ku Muhammad Naim, Ku Khalif Adam Shariff Adli, Aminuddin Ahmad Syafadhli, Abu Bakar Noor Zuraidin, Mohd Safar Alexander, Gegov
author_facet	Ku Muhammad Naim, Ku Khalif Adam Shariff Adli, Aminuddin Ahmad Syafadhli, Abu Bakar Noor Zuraidin, Mohd Safar Alexander, Gegov
author_sort	Ku Muhammad Naim, Ku Khalif
title	A reliability based consistent fuzzy preference relations – fuzzy similarity for risk assessment in oil and gas industry
title_short	A reliability based consistent fuzzy preference relations – fuzzy similarity for risk assessment in oil and gas industry
title_full	A reliability based consistent fuzzy preference relations – fuzzy similarity for risk assessment in oil and gas industry
title_fullStr	A reliability based consistent fuzzy preference relations – fuzzy similarity for risk assessment in oil and gas industry
title_full_unstemmed	A reliability based consistent fuzzy preference relations – fuzzy similarity for risk assessment in oil and gas industry
title_sort	reliability based consistent fuzzy preference relations – fuzzy similarity for risk assessment in oil and gas industry
publishDate	2019
url	http://umpir.ump.edu.my/id/eprint/26489/1/78.%20A%20reliability%20based%20consistent%20fuzzy%20preference%20relations.pdf http://umpir.ump.edu.my/id/eprint/26489/2/78.1%20A%20reliability%20based%20consistent%20fuzzy%20preference%20relations.pdf http://umpir.ump.edu.my/id/eprint/26489/
_version_	1654960240498573312
score	13.211869

A reliability based consistent fuzzy preference relations – fuzzy similarity for risk assessment in oil and gas industry

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