A Rule-Based Inference Method Using Dempster-Shafer Theory

被引：2
|
作者：
Jin, Liuqian [1 ]
Xu, Yang [2 ]
机构：
[1] Southwest Jiaotong Univ, Intelligent Control Dev Ctr, Chengdu 610031, Peoples R China
[2] Southwest Jiaotong Univ, Sch Econ & Management, Chengdu 610031, Peoples R China
来源：
KNOWLEDGE ENGINEERING AND MANAGEMENT , ISKE 2013 | 2014年 / 278卷
基金：
美国国家科学基金会;
关键词：
Uncertainty reasoning; Dempster-Shafer theory; Knowledge representation; Rule-base; Interval number; EVIDENTIAL REASONING APPROACH;
D O I：
10.1007/978-3-642-54930-4_7
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The Dempster-Shafer theory of evidence for attribute aggregation provides a method to deal with uncertainty reasoning. In this paper, uncertainty reasoning method based on rule-base with certainty interval is investigated. First, knowledge representation with interval uncertainty is defined and the matching principle is given. Then, a rule-based inference method under interval numbers using Dempster-Shafer theory is derived. A numerical example is examined to show the implementation process of the proposed method.
引用
收藏
页码：61 / 72
页数：12
相关论文
共 50 条
  • [21] Footstep Detection using Dempster-Shafer Theory
    Achroufene, Achour
    Melchane, Selestine
    Ameziane, Fahem
    PROGRAM OF THE 2ND INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND AUTOMATIC CONTROL, ICEEAC 2024, 2024,
  • [22] A generalization of entropy using Dempster-Shafer theory
    Herencia, JA
    Lamata, MT
    INTERNATIONAL JOURNAL OF GENERAL SYSTEMS, 2000, 29 (05) : 719 - 735
  • [23] A modified combination rule to conflict evidence for Dempster-Shafer theory
    Su, Xiangyang
    Dong, Zengshou
    2015 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (CICN), 2015, : 993 - 996
  • [24] AN EXERCISE IN DEMPSTER-SHAFER THEORY
    HAJEK, P
    HARMANEC, D
    INTERNATIONAL JOURNAL OF GENERAL SYSTEMS, 1992, 20 (02) : 137 - 142
  • [25] A flexible rule for evidential combination in Dempster-Shafer theory of evidence
    Ma, Wenjun
    Jiang, Yuncheng
    Luo, Xudong
    APPLIED SOFT COMPUTING, 2019, 85
  • [26] A clash in Dempster-Shafer theory
    Xiong, W
    Ju, S
    Luo, X
    10TH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-3: MEETING THE GRAND CHALLENGE: MACHINES THAT SERVE PEOPLE, 2001, : 793 - 796
  • [27] Geospatial Modeling Using Dempster-Shafer Theory
    Elmore, Paul A.
    Petry, Frederick E.
    Yager, Ronald R.
    IEEE TRANSACTIONS ON CYBERNETICS, 2017, 47 (06) : 1551 - 1561
  • [28] Sensor fusion using Dempster-Shafer theory
    Wu, HD
    Siegel, M
    Stiefelhagen, R
    Yang, J
    IMTC 2002: PROCEEDINGS OF THE 19TH IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, VOLS 1 & 2, 2002, : 7 - 12
  • [29] Object Classification Using Dempster-Shafer Theory
    Harasymowicz-Boggio, B.
    Siemiatkowska, B.
    MECHATRONICS 2013: RECENT TECHNOLOGICAL AND SCIENTIFIC ADVANCES, 2014, : 559 - 565
  • [30] Fundamentals of the Dempster-Shafer Theory
    Peri, Joseph S. J.
    SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION XXI, 2012, 8392
12345