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An interval method to measure the uncertainty of basic probability assignment

  • Fuzzy systems and their mathematics
  • Published:
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Abstract

Comparing the probability distribution, basic probability assignment in evidence theory is more efficient to deal with uncertain information. However, the uncertainty measure of basic probability assignment is still an open issue. In this paper, a new uncertainty measure based on Tsallis entropy is proposed to solve problems when the basic probability assignments are not given or being transformed into interval probability distribution. The proposed entropy is an extension of Tsallis entropy in continuous space. Some numerical examples are illustrated to show the efficiency of the proposed method.

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Acknowledgements

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

Funding

Funding was provided by innovative research group project of the national natural science foundation of China (Grant No. 61973332).

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Authors and Affiliations

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

    Jinyan Su

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

    Jinyan Su & Yong Deng

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

    Yong Deng

Authors
  1. Jinyan Su
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  2. Yong Deng
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Contributions

JYS performed the experiments and wrote the manuscript, YD contributed to the central idea and concept of the study while providing critical revisions for the paper.

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Correspondence to Yong Deng.

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Su, J., Deng, Y. An interval method to measure the uncertainty of basic probability assignment. Soft Comput 26, 6041–6050 (2022). https://doi.org/10.1007/s00500-022-07114-8

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