Belief Interval-Based Distance Measures in the Theory of Belief Functions
Belief Interval-Based Distance Measures in the Theory of Belief Functions
复制标题
置信函数理论中基于置信区间的距离测量
DOI：
10.1109/tsmc.2016.2628879
复制
发表时间：
2018-06-01
影响因子：
8.7
通讯作者：
Yang, Yi
中科院分区：
文献类型：
--
作者：
Han, Deqiang;Dezert, Jean;Yang, Yi
在信念函数相关领域中，距离测度是一个重要的概念，它表示证据体之间的相异程度。各种证据距离度量已经被提出并广泛应用于各种信念函数相关的应用中，特别是在性能评估中。严格和非严格证据距离度量的现有定义各有优缺点。在本文中，我们基于焦点元素信念区间之间的 Wasserstein 距离，提出了两个基本信念分配之间的两种新的严格证据距离度量（欧几里德形式和切比雪夫形式）。提供了说明性例子、模拟、应用和相关分析，以证明我们提出的证据距离措施的合理性和有效性。
In belief functions related fields, the distance measure is an important concept, which represents the degree of dissimilarity between bodies of evidence. Various distance measures of evidence have been proposed and widely used in diverse belief function related applications, especially in performance evaluation. Existing definitions of strict and nonstrict distance measures of evidence have their own pros and cons. In this paper, we propose two new strict distance measures of evidence (Euclidean and Chebyshev forms) between two basic belief assignments based on the Wasserstein distance between belief intervals of focal elements. Illustrative examples, simulations, applications, and related analyses are provided to show the rationality and efficiency of our proposed measures for distance of evidence.