Evidence conflict measurement method based on Pignistic probability transformation and singular value decomposition

Xinglin GUO; Zhenxiao SUN; Yuyao ZHOU; Lianzhi QI; Yi ZHANG

doi:10.11959/j.issn.1000-436x.2021086

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Evidence conflict measurement method based on Pignistic probability transformation and singular value decomposition

Papers | 更新时间：2024-06-05

- Evidence conflict measurement method based on Pignistic probability transformation and singular value decomposition
- Journal on Communications Vol. 42, Issue 4, Pages: 150-157(2021)
- 作者机构：
  
  中国工程物理研究院计算机应用研究所，四川绵阳 621900
- 作者简介：
- 基金信息：
  
  The Technical Basic Research Project of State Administration of Science, Technology and Industry for National Defence(JSZL2015212B001)
- DOI：10.11959/j.issn.1000-436x.2021086
  CLC： TP391
- Online First：2021-04，
  
  Published：25 April 2021
- 稿件说明：
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Xinglin GUO, Zhenxiao SUN, Yuyao ZHOU, et al. Evidence conflict measurement method based on Pignistic probability transformation and singular value decomposition[J]. Journal on Communications, 2021, 42(4): 150-157.
DOI：

Xinglin GUO, Zhenxiao SUN, Yuyao ZHOU, et al. Evidence conflict measurement method based on Pignistic probability transformation and singular value decomposition[J]. Journal on Communications, 2021, 42(4): 150-157. DOI： 10.11959/j.issn.1000-436x.2021086.

摘要

针对常见证据冲突度量方法适应性差、准确性低的问题，提出了一种基于Pignistic概率转换和奇异值分解的证据冲突度量方法。首先通过Pignistic概率转换将证据焦元差异映射到信度差异上，构建证据复合信任函数矩阵。然后采用奇异值分解的方法提取矩阵特征，根据奇异值特性将矩阵特征空间划分为相似子空间和冲突子空间，综合考虑证据矩阵相似特性和冲突特性，将冲突子空间奇异值与相似子空间奇异值之比作为新的冲突度量因子。最后在全冲突场景、变信度场景、变焦元场景、焦元嵌套场景等多种证据冲突场景下将所提方法与常见方法进行了对比分析，结果表明所提方法具有适应性广、准确性高、稳定性好的特点。

Abstract

In view of the problem of poor adaptability and low accuracy of common evidence conflict measurement method

an evidence conflict measurement method based on Pignistic probability transformation and singular value decomposition was proposed.First

Pignistic probability transformation was used to map the evidence focal element difference to the belief difference

and the evidence composite belief function matrix was constructed.Then

the matrix features were extracted by singular value decomposition

and the matrix feature space was divided into similar subspace and conflict subspace according to singular value characteristics.Considering the similarity and conflict characteristics of the evidence matrix

and the ratio of the singular value of the conflict subspace to the singular value of the similar subspace was taken as the new conflict measure factor.Finally

the proposed method was compared with common methods in various evidence conflict scenarios

such as full conflict scenario

variable reliability scenario

variable focus element scenario

focal element nested scenario

and the results show that the proposed method has wide adaptability

high accuracy and good stability.

关键词

Keywords

references

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