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

Ku Khalif, Ku Muhammad Naim and Abu Bakar, Ahmad Syafadhli and Gegov, Alexander and Aminuddin, Adam Shariff Adli and Mohd Safar, Noor Zuraidin (2019) A reliability based consistent fuzzy preference relations for risk assessment in oil and gas industry. In: 9th Int. Conf. on Geotechnique, Construction Materials and Environment, 20-22 November 2019, Tokyo, Japan.

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Abstract

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. Z-numbers 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 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 and 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 under fuzzy environment.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Multi criteria decision making;consistent fuzzy preference relations; z-numbers;reliability;risk assessment; oil and gas industry
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ212-225 Control engineering systems. Automatic machinery (General)
Divisions:	Faculty of Computer Science and Information Technology > Department of Information Security
Depositing User:	Mrs. Normardiana Mardi
Date Deposited:	02 Nov 2021 03:24
Last Modified:	02 Nov 2021 03:24
URI:	http://eprints.uthm.edu.my/id/eprint/3469

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