运筹与管理 ›› 2022, Vol. 31 ›› Issue (3): 132-137.DOI: 10.12005/orms.2022.0089

• 应用研究 • 上一篇    下一篇

基于改进证据理论的绩效综合评价模型及其应用

沈延安1, 张君彪2   

  1. 1.陆军炮兵防空兵学院 无人机应用系,安徽 合肥 230031;
    2.空军预警学院 预警情报系,湖北 武汉 430000
  • 收稿日期:2019-07-23 出版日期:2022-03-25 发布日期:2022-04-12
  • 通讯作者: 张君彪(1995-),男,博士研究生,主要研究方向为预警情报分析、目标跟踪与预测。
  • 作者简介:沈延安(1978-),男,教授,博士,主要研究方向为管理工程、无人机故障诊断。
  • 基金资助:
    全军军事类研究生资助课题(JY2019B138)

Comprehensive Performance Evaluation Model Based on Improved Evidence Theory and Its Application

SHEN Yan-an1, ZHANG Jun-biao2   

  1. 1. UAV Application Department, Army Artillery and Air Defense Corps Academy, Hefei 230031, China;
    2. Early Warning Intelligence Department, Air Force Early Warning Academy, Wuhan 430000, China
  • Received:2019-07-23 Online:2022-03-25 Published:2022-04-12

摘要: 针对复杂管理系统要素种类多样、主客观信息并存、难以定量评价的问题,提出了一种改进证据理论的绩效综合评价模型。该模型提出了基于云模型-二元语义的基本概率分配生成与表示方法,设计了一种基于Tanimoto测度的证据相似度测量公式来确定各证据冲突程度,然后根据证据权值修正证据源,最后采用改进的证据合成公式进行融合。实际算例表明,该综合评价模型在处理多属性、多层次的复杂系统评价问题上更具有效性和实用性。

关键词: 证据理论, 云模型, 二元语义, 综合评价

Abstract: In view of the various factors of complex management system, the coexistence of subjective and objective information and the difficulty of quantitative evaluation, a comprehensive performance evaluation model based on improved evidence theory is proposed. Firstly, the cloud model and two-tuple linguistic is proposed to transform evaluation information into basic probability assignment. Then, the Tanimoto measure is introduced, and a formula for measuring evidence similarity is designed to determine the conflict degree between two pieces of evidence. After that, the original evidence is revised and weighted based on this credibility. Finally, the fusion is accomplished by adopting the improved evidence combination formula. Numerical example illustrates that the comprehensive evaluation model is more effective and practical in dealing with the multi-attribute and multi-level complex system evaluation problem.

Key words: evidence theory, cloud model, two-tuple linguistic, comprehensive evaluation

中图分类号: