A new interval constructed belief rule base with rule reliability

被引:9
|
作者
Cheng, Xiaoyu [1 ]
Han, Peng [1 ]
He, Wei [1 ,2 ]
Zhou, Guohui [1 ]
机构
[1] Harbin Normal Univ, Sch Comp Sci & Informat Engn, Harbin 150025, Peoples R China
[2] High Tech Inst Xian, Xian 710025, Shanxi, Peoples R China
来源
JOURNAL OF SUPERCOMPUTING | 2023年 / 79卷 / 14期
基金
中国博士后科学基金;
关键词
Belief rule base; Combination rule explosion; Rule reliability; Complex system; Liquid launch vehicle; OPTIMIZATION; PREDICTION; SYSTEM; MODEL;
D O I
10.1007/s11227-023-05284-2
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The combination rule explosion problem of belief rule base (BRB) is a difficult problem to solve in complex systems and has attracted wide attention. A new interval-constructed belief rule base with rule reliability (IBRB-r) is proposed to solve the problem of combination rule explosion in belief rule base. This model not only proposes a new interval rule construction method, but also designs a new interval rule inference process with rule reliability. This approach can not only clearly indicate the contribution degree of each rule to the model, but also solve the problem of combination rule explosion. This is because combining rules in interval addition form avoids the exponential growth in the number of rules caused by combining rules in Cartesian product form. Therefore, IBRB-r is more suitable for complex system modeling. In the case study section, the structural safety assessment of liquid launch vehicle is introduced to conduct a concrete example analysis. Experimental results show that the proposed model achieves over 95% accuracy under the liquid rocket dataset and has relatively higher accuracy under other datasets as well.
引用
收藏
页码:15835 / 15867
页数:33
相关论文
共 50 条
  • [41] A new belief rule base knowledge representation scheme and inference methodology using the evidential reasoning rule for evidence combination
    AbuDahab, Khalil
    Xu, Dong-ling
    Chen, Yu-wang
    EXPERT SYSTEMS WITH APPLICATIONS, 2016, 51 : 218 - 230
  • [42] A belief rule base approach for smart traffic lights
    Lin, Yan-Qing
    Li, Min
    Chen, Xiao-Cong
    Fu, Yang-Geng
    Chi, Zi-Wen
    PROCEEDINGS OF 2016 9TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 1, 2016, : 460 - 463
  • [43] A Survey of Belief Rule-Base Expert System
    Zhou, Zhi-Jie
    Hu, Guan-Yu
    Hu, Chang-Hua
    Wen, Cheng-Lin
    Chang, Lei-Lei
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (08): : 4944 - 4958
  • [44] A Novel Construction and Inference Methodology of Belief Rule Base
    Hu, Qingshuang
    Li, Chenghai
    Lu, Yanli
    Li, Song
    IEEE ACCESS, 2020, 8 (08): : 209738 - 209749
  • [45] Circuit Tolerance Design Using Belief Rule Base
    Xu, Xiao-Bin
    Liu, Zheng
    Chen, Yu-Wang
    Xu, Dong-Ling
    Wen, Cheng-Lin
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, 2015
  • [46] A novel game-based belief rule base
    Chen, Haobing
    He, Wei
    Zhou, Guohui
    Cui, Yanling
    Gao, Ming
    Qian, Jidong
    Liang, Minjie
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 254
  • [47] Parallel multipopulation optimization for belief rule base learning
    Zhu, Wei
    Chang, Leilei
    Sun, Jianbin
    Wu, Guohua
    Xu, Xiaobin
    Xu, Xiaojian
    INFORMATION SCIENCES, 2021, 556 : 436 - 458
  • [48] A Novel Modeling Approach for Cumulative Belief Rule-Base With Joint Optimization and Rule Synthesis
    Yang, Long-Hao
    Yu, Dan-Ning
    Ye, Fei-Fei
    Hu, Haibo
    Ye, Qingqing
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2025, 55 (04): : 2961 - 2973
  • [49] Rule Reduction in Air Combat Belief Rule Base Based on Fuzzy-rough Set
    Wu, Baibing
    Huang, Jian
    Gao, Wanying
    Kong, Jiangtao
    2016 3RD INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE), 2016, : 593 - 596
  • [50] An extended belief rule-based system with hybrid sampling strategy for imbalanced rule base
    Hou, Bingbing
    Fu, Chao
    Xue, Min
    INFORMATION SCIENCES, 2024, 684