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Evidential global linguistic terms entropy

  • Fuzzy systems and their mathematics
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Abstract

In this paper, we consider a more comprehensive entropy measure for linguistic mass function, which is called evidential global linguistic terms entropy (EGLTE). This proposed new entropy considers the uncertainty caused by the linguistic terms as well as the mass function, and uses a discount rate to express their weight in the final uncertainty. The discount rate is determined by the unambiguity degree of the linguistic set. With a fixed discount rate, the situation when the evidential global linguistic terms entropy (EGLTE) reaches its maximum is also discussed in our paper. Some numerical examples and its application in multiple attribute decision making about determining objective weights are given to illustrate the accuracy and utility of the proposed entropy measure.

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Acknowledgements

The work is partially supported by National Natural Science Foundation of China (Grant No. 61973332).

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The authors have not disclosed any funding.

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Authors and Affiliations

  1. Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Jinyan Su & Yong Deng

  2. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Jinyan Su

  3. School of Education, Shannxi Normal University, Xi’an, 710062, China

    Yong Deng

  4. School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, 923-1211, Japan

    Yong Deng & Nam-Van Huynh

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  1. Jinyan Su
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Correspondence to Yong Deng.

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Su, J., Deng, Y. & Huynh, NV. Evidential global linguistic terms entropy. Soft Comput 27, 227–237 (2023). https://doi.org/10.1007/s00500-022-07580-0

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