一种新的信念函数散度测度及其应用

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, THEORY & METHODS

International Journal of General Systems Pub Date : 2022-12-01 DOI:10.1080/03081079.2022.2151006

Manpreet Kaur, Amit Kumar Srivastava

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引用次数: 2

摘要

不确定和复杂环境下的信息融合具有很高的挑战性。Dempster-Shafer (D-S)证据理论已经被许多研究者成功地应用于多传感器数据融合中。然而，在证据高度矛盾的情况下，它会产生反直觉的结果。本文给出了一种新的非负的、对称的、满足三角不等式的信念函数的散度测度。利用所提出的散度测度，讨论了一种结合不同基本概率分配的算法，并将其应用于目标识别系统和分类问题。

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A new divergence measure for belief functions and its applications

ABSTRACT Information fusion in uncertain and complex environments is highly challenging. Dempster–Shafer (D-S) evidence theory has been successfully applied by various researchers in multi-sensor data fusion. However, it yields counterintuitive results in case of highly conflicting evidence. In this paper, we have developed a new divergence measure for belief functions that is nonnegative, symmetric, and satisfies the triangle inequality. Using the developed divergence measure, an algorithm for combining distinct basic probability assignments (BPAs) has been discussed and applied in target recognition systems and classification problems.

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来源期刊

International Journal of General Systems 工程技术-计算机：理论方法

CiteScore

4.10

自引率

20.00%

发文量

审稿时长

6 months

期刊介绍： International Journal of General Systems is a periodical devoted primarily to the publication of original research contributions to system science, basic as well as applied. However, relevant survey articles, invited book reviews, bibliographies, and letters to the editor are also published. The principal aim of the journal is to promote original systems ideas (concepts, principles, methods, theoretical or experimental results, etc.) that are broadly applicable to various kinds of systems. The term “general system” in the name of the journal is intended to indicate this aim–the orientation to systems ideas that have a general applicability. Typical subject areas covered by the journal include: uncertainty and randomness; fuzziness and imprecision; information; complexity; inductive and deductive reasoning about systems; learning; systems analysis and design; and theoretical as well as experimental knowledge regarding various categories of systems. Submitted research must be well presented and must clearly state the contribution and novelty. Manuscripts dealing with particular kinds of systems which lack general applicability across a broad range of systems should be sent to journals specializing in the respective topics.