基于改进证据理论的模糊贝叶斯网络及其应用

许子诺; 刘尉; 安彦蓉; 王彧

doi:10.13568/j.cnki.651094.651316.2024.04.15.0001

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基于改进证据理论的模糊贝叶斯网络及其应用

数理科学 | 更新时间：2026-01-21

- 基于改进证据理论的模糊贝叶斯网络及其应用
- 基于改进证据理论的模糊贝叶斯网络及其应用
- 新疆大学学报（自然科学版中英文） 2025年42卷第2期页码：156-167
- 作者机构：
  
  1. 河海大学数学学院
  2. 南京邮电大学管理学院
- 作者简介：
- 基金信息：
  
  江苏省双创博士项目“包容性管理对多团队协同创新的影响研究”（JSSCBS210499）;南京邮电大学引进人才科研启动资金（人文社科类）“多团队协同创新下包容型领导的形成、过程与影响机制”（NYY221014）;江苏省高校哲学社会科学项目“国有企业主导创新生态系统的构建机制与韧性评价研究”（2023SJYB0125）
- DOI：10.13568/j.cnki.651094.651316.2024.04.15.0001
  中图分类号： O212.8
- 纸质出版：2025
- 稿件说明：
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[1]许子诺,刘尉,安彦蓉,等.基于改进证据理论的模糊贝叶斯网络及其应用[J].新疆大学学报(自然科学版中英文),2025,42(02):156-167.
[1]许子诺,刘尉,安彦蓉,等.基于改进证据理论的模糊贝叶斯网络及其应用[J].新疆大学学报(自然科学版中英文),2025,42(02):156-167. DOI： 10.13568/j.cnki.651094.651316.2024.04.15.0001.

DOI：10.13568/j.cnki.651094.651316.2024.04.15.0001.

摘要

针对模糊贝叶斯网络中先验概率输入的不确定性问题，通过证据理论对专家意见进行融合，得到更加可靠的先验概率．同时，提出一种证据理论的改进方法，解决证据理论不能处理高冲突数据的问题，从而降低专家意见的融合冲突，使专家意见可以合理且充分地融合．最后，通过人类可信性分析的相关实例验证理论的合理性，并通过与不同方法对比，说明所提融合方法的可行性和优势．

Abstract

To address the uncertainty issue of prior probability inputs in fuzzy Bayesian network

this paper proposes a method to obtain more reliable prior probabilities by integrating expert opinions using evidence theory.Additionally

an improved method of evidence theory is introduced to tackle the problem of high-conflict data that traditional evidence theory cannot handle

thereby reducing the conflict in the integration of expert opinions and enabling their rational and sufficient fusion. Finally

the rationality of the proposed theory is validated through relevant examples of human credibility analysis

and its feasibility and advantages are demonstrated by comparing with other methods.

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Keywords

references

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