Interval-Valued Belief Rule Inference Methodology Based on Evidential Reasoning-IRIMER

被引:11
作者
Zhu, Hua [1 ]
Zhao, Jianbin [1 ]
Xu, Yang [2 ]
Du, Limin [2 ]
机构
[1] Zhengzhou Univ, Sch Math & Stat, Zhengzhou 450001, Henan, Peoples R China
[2] Southwest Jiaotong Univ, Intelligent Control Dev Ctr, Chengdu 610031, Sichuan, Peoples R China
关键词
Belief rule base (BRB); interval-valued belief rule base; evidential reasoning (ER) approach; interval-valued evidential reasoning (IER) approach; nonlinear optimization; INTUITIONISTIC FUZZY-SETS; DECISION-ANALYSIS; SYSTEM; PREFERENCES; REPRESENTATION; OPTIMIZATION; FRAMEWORK; WEIGHTS; MODEL;
D O I
10.1142/S0219622016500322
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, an interval-valued belief rule inference methodology based on evidential reasoning (IRIMER) is proposed, which includes the interval-valued belief rule representation scheme and its inference methodology. This interval-valued belief rule base is designed with interval-valued belief degrees embedded in both the consequents and the antecedents of each rule, which can represent uncertain information or knowledge more flexible and reasonable than the previous belief rule base. Then its inference methodology is developed on the interval-valued evidential reasoning (IER) approach. The IRIMER approach improves and extends the recently uncertainty inference methods from the rule representation scheme and the inference framework. Finally, a case is studied to demonstrate the concrete implementation process of the IRIMER approach, and comparison analysis shows that the IRIMER approach is more flexible and effective than the RIMER [J. B. Yang, J. Liu, J. Wang, H. S. Sii and H. W. Wang, Belief rule-base interference methodology using the evidential reasoning approach-RIMER, IEEE Transaction on Systems Man and Cybernetics Part A-Systems and Humans 36 (2006) 266-285.] approach and the ERIMER [J. Liu, L. Martinez, A. Calzada and H. Wang, A novel belief rule base representation, generation and its inference methodology, Knowledge-Based Systems 53 (2013) 129-141.] approach.
引用
收藏
页码:1345 / 1366
页数:22
相关论文
共 50 条
  • [1] Comparative study of fuzzy evidential reasoning and fuzzy rule-based approaches: an illustration for water quality assessment in distribution networks
    Aghaarabi, E.
    Aminravan, F.
    Sadiq, R.
    Hoorfar, M.
    Rodriguez, M. J.
    Najjaran, H.
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2014, 28 (03) : 655 - 679
  • [2] IVTURS: A Linguistic Fuzzy Rule-Based Classification System Based On a New Interval-Valued Fuzzy Reasoning Method With Tuning and Rule Selection
    Antonio Sanz, Jose
    Fernandez, Alberto
    Bustince, Humberto
    Herrera, Francisco
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2013, 21 (03) : 399 - 411
  • [3] Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning
    Antonio Sanz, Jose
    Fernandez, Alberto
    Bustince, Humberto
    Herrera, Francisco
    [J]. INFORMATION SCIENCES, 2010, 180 (19) : 3674 - 3685
  • [4] INTERVAL VALUED INTUITIONISTIC FUZZY-SETS
    ATANASSOV, K
    GARGOV, G
    [J]. FUZZY SETS AND SYSTEMS, 1989, 31 (03) : 343 - 349
  • [5] Belief rule-based system for portfolio optimisation with nonlinear cash-flows and constraints
    Chen, Yu-Wang
    Poon, Ser-Huang
    Yang, Jian-Bo
    Xu, Dong-Ling
    Zhang, Dongxu
    Acomb, Simon
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2012, 223 (03) : 775 - 784
  • [6] Integrated evidential reasoning approach in the presence of cardinal and ordinal preferences and its applications in software selection
    Chin, Kwai-Sang
    Fu, Chao
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (15) : 6718 - 6727
  • [7] UPPER AND LOWER PROBABILITIES INDUCED BY A MULTIVALUED MAPPING
    DEMPSTER, AP
    [J]. ANNALS OF MATHEMATICAL STATISTICS, 1967, 38 (02): : 325 - &
  • [8] Denoeux T, 1999, INT J APPROX REASON, V20, P79, DOI 10.1016/S0888-613X(98)10023-3
  • [9] A new approach to the rule-base evidential reasoning in the intuitionistic fuzzy setting
    Dymova, Ludmila
    Sevastjanov, Pavel
    [J]. KNOWLEDGE-BASED SYSTEMS, 2014, 61 : 109 - 117
  • [10] An interval difference based evidential reasoning approach with unknown attribute weights and utilities of assessment grades
    Fu, Chao
    Wang, Yingming
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2015, 81 : 109 - 117