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In this paper, we introduce a novel distance measure within the framework of Dempster-Shafer theory for quantifying the dissimilarity between two basic belief assignments. To demonstrate its effectiveness, the proposed method is compared with several widely used approaches using illustrative examples. Additionally, it is applied to uncertainty representation in numerical approximations of ODE solutions and in the analysis of biological data.

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Distance Between m-Functions in Dempster-Shafer Theory

  • 会议论文

  • 发表日期：

    2025年

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  • Minyi Chen,
  • Yanyan He,
  • Isai Chavarri,
  • Lindsay Waldrop

摘要

In this paper, we introduce a novel distance measure within the framework of Dempster-Shafer theory for quantifying the dissimilarity between two basic belief assignments. To demonstrate its effectiveness, the proposed method is compared with several widely used approaches using illustrative examples. Additionally, it is applied to uncertainty representation in numerical approximations of ODE solutions and in the analysis of biological data.