Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4944977 | Information Sciences | 2016 | 35 Pages |
Abstract
The main objective of this contribution is to develop information about how entropy measures of linguistic terms can be designed. Two different ideas have been put forward to explain this designation: (1) The idea that comes from the seminal definition of fuzziness measure; (2) The idea of transforming similarity measures to entropy ones. To demonstrate the utility and effectiveness of the proposed entropy measures, an entropy-based approach of determining objective weights of attributes is developed to solve multiple-attribute decision-making problems in the context of linguistic term sets.
Keywords
Related Topics
Physical Sciences and Engineering
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Artificial Intelligence
Authors
B. Farhadinia,