An unsupervised technique to estimate λ0-fuzzy measure values and its application to multi-criteria decision making
The use of Choquet integral as an aggregation operator in multi-criteria decision-making problems requires the prior estimation of fuzzy measure values. λ0 -measure is one form of fuzzy measure which was introduced to reduce the usual computational complexity associated with the estimation of fuzzy...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | http://repo.uum.edu.my/27240/1/ICIEA%202020%20969%20973.pdf http://repo.uum.edu.my/27240/ http://doi.org/10.1109/ICIEA49774.2020.9102098 |
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| Summary: | The use of Choquet integral as an aggregation operator in multi-criteria decision-making problems requires the prior estimation of fuzzy measure values. λ0 -measure is one form of fuzzy measure which was introduced to reduce the usual computational complexity associated with the estimation of fuzzy measure values. However, the existing techniques to estimate λ0 -measure require some amount of initial data from the decision-makers. This paper, therefore, aimed at proposing a completely unsupervised estimation technique, where the λ0- measure values are directly derived based on the available decision matrix, without the need for any initial data from the decision-makers. The technique was developed by incorporating the CRITIC method into the original λ0 - measure estimation technique. The usage of the proposed technique was illustrated based on a university course evaluation problem. The same problem was also solved with a conventional additive operator for the comparison purpose. |
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