犹豫模糊距离测度分析及其在决策层融合识别中的应用

于淼; 孙贵东; 李双明

doi:10.12263/DZXB.20220938

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犹豫模糊距离测度分析及其在决策层融合识别中的应用

学术论文 | 更新时间：2026-04-10

- 犹豫模糊距离测度分析及其在决策层融合识别中的应用
- Distance Analysis of Hesitant Fuzzy Set and Its Application in Fusion Recognition on Decision Making Level
- 电子学报 2024年52卷第1期页码：181-192
- 作者机构：
  
  1.中国人民解放军某部,北京 100000
  2.中国人民解放军32801部队,北京 100082
  3.中国人民解放军92941部队,辽宁葫芦岛 125001
- 作者简介：
  
  [ "于淼女，1980年生，北京人.中国人民解放军某部工程师.主要研究方向为信息与通信工程. E-mail: moppetnizi@163.com" ]
  [ "孙贵东男，1989年生，山东荣成人.中国人民解放军32801部队助理研究员.主要研究方向为复杂电磁环境、信息融合与智能决策. E-mail: sdwhsgd@163.com" ]
  [ "李双明男，1986年生，山东梁山人.中国人民解放军92941部队工程师.主要研究方向为智能识别、不确定信息处理.E-mail: aminglishuang@126.com" ]
- 基金信息：
  
  国家自然科学基金青年科学基金项目(62001503)
- DOI：10.12263/DZXB.20220938
  中图分类号： TP391;O235
- 收稿：2022-08-09，
  
  修回：2022-10-09，
  
  纸质出版：2024-01-25
- 稿件说明：
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于淼,孙贵东,李双明.犹豫模糊距离测度分析及其在决策层融合识别中的应用[J].电子学报,2024,52(01):181-192.

YU Miao, SUN Gui-dong, LI Shuang-ming.Distance Analysis of Hesitant Fuzzy Set and Its Application in Fusion Recognition on Decision Making Level[J].Acta Electronica Sinica, 2024, 52(01): 181-192.
于淼,孙贵东,李双明.犹豫模糊距离测度分析及其在决策层融合识别中的应用[J].电子学报,2024,52(01):181-192. DOI：10.12263/DZXB.20220938

YU Miao, SUN Gui-dong, LI Shuang-ming.Distance Analysis of Hesitant Fuzzy Set and Its Application in Fusion Recognition on Decision Making Level[J].Acta Electronica Sinica, 2024, 52(01): 181-192. DOI：10.12263/DZXB.20220938

摘要

现有的犹豫模糊距离测度大多数受犹豫模糊数隶属度个数延拓补值和顺序重排条件的限制，在一定条件下导致度量结果不准确.为此，本文提出基于距离矩阵的犹豫模糊距离测度，分析了现有犹豫模糊比较法则的局限性，定义了新的全序比较法则；提出了距离矩阵概念，合理解释了现有犹豫模糊距离测度的不足.结合犹豫模糊新比较法则、新提出的特征距离、前景理论和集成算子，形成了CDPA（Comparison，Distance，Prospect，Aggregation）识别决策新方法，并应用于决策层融合识别解决目标威胁判定问题.结果表明，该距离测度能够解决延拓补值和顺序重排的问题，识别准确.

Abstract

Most of the existing distance measures for the HFS (Hesitant Fuzzy Set) and its extensions either require the length of the membership in the HFEs (Hesitant Fuzzy Elements) to be equal or need to rearrange the order

which result in error and information loss under certain circumstances. In order to solve these problems

we propose a distance measure of HFS based on distance matrix. The limitations of the existing hesitant fuzzy comparison rules are analyzed

and a new total order comparison rule is defined. The proposed distance can reasonably explain the shortcomings of the existing hesitant fuzzy distance measures. Furthermore

we explore a CDPA (Comparison

Distance

Prospect

Aggregation) method by using a new comparison law

the proposed characteristic distance measure

prospect theory notion and aggregation operators. Finally

we apply the CDPA method to the decision making level target recognition and solve a target threat judgment problem. The results show that the proposed method can liberate the length and order to obtain correct recognition.

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Keywords

references

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