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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
