A reliability based consistent fuzzy preference relations 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. Z-numbers is proposed to model the uncertainty produced by...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/3469/1/KP%202020%20%2873%29.pdf |
| _version_ | 1796868842699358208 |
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| author | Ku Khalif, Ku Muhammad Naim Abu Bakar, Ahmad Syafadhli Gegov, Alexander Aminuddin, Adam Shariff Adli Mohd Safar, Noor Zuraidin |
| author_facet | Ku Khalif, Ku Muhammad Naim Abu Bakar, Ahmad Syafadhli Gegov, Alexander Aminuddin, Adam Shariff Adli Mohd Safar, Noor Zuraidin |
| author_sort | Ku Khalif, Ku Muhammad Naim |
| collection | UTHM |
| 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. 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. |
| first_indexed | 2024-03-05T21:45:53Z |
| format | Conference or Workshop Item |
| id | uthm.eprints-3469 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-03-05T21:45:53Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | uthm.eprints-34692021-11-02T03:24:17Z http://eprints.uthm.edu.my/3469/ A reliability based consistent fuzzy preference relations for risk assessment in oil and gas industry Ku Khalif, Ku Muhammad Naim Abu Bakar, Ahmad Syafadhli Gegov, Alexander Aminuddin, Adam Shariff Adli Mohd Safar, Noor Zuraidin TJ212-225 Control engineering systems. Automatic machinery (General) 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. 2019 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/3469/1/KP%202020%20%2873%29.pdf 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. |
| spellingShingle | TJ212-225 Control engineering systems. Automatic machinery (General) Ku Khalif, Ku Muhammad Naim Abu Bakar, Ahmad Syafadhli Gegov, Alexander Aminuddin, Adam Shariff Adli Mohd Safar, Noor Zuraidin A reliability based consistent fuzzy preference relations for risk assessment in oil and gas industry |
| title | A reliability based consistent fuzzy preference relations for risk assessment in oil and gas industry |
| title_full | A reliability based consistent fuzzy preference relations for risk assessment in oil and gas industry |
| title_fullStr | A reliability based consistent fuzzy preference relations for risk assessment in oil and gas industry |
| title_full_unstemmed | A reliability based consistent fuzzy preference relations for risk assessment in oil and gas industry |
| title_short | A reliability based consistent fuzzy preference relations for risk assessment in oil and gas industry |
| title_sort | reliability based consistent fuzzy preference relations for risk assessment in oil and gas industry |
| topic | TJ212-225 Control engineering systems. Automatic machinery (General) |
| url | http://eprints.uthm.edu.my/3469/1/KP%202020%20%2873%29.pdf |
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