The Interpretability of Rule-based Modeling Approach and Its Development

被引:0
|
作者
Zhou Z.-J. [1 ]
Cao Y. [1 ]
Hu C.-H. [1 ]
Tang S.-W. [1 ]
Zhang C.-C. [1 ]
Wang J. [1 ]
机构
[1] Missile Engineering College, Rocket Force University of Engineering, Xi'an
来源
Zidonghua Xuebao/Acta Automatica Sinica | 2021年 / 47卷 / 06期
基金
中国国家自然科学基金;
关键词
Interpretability; Rule-based modeling approach; System modeling; Uncertainty;
D O I
10.16383/j.aas.c200402
中图分类号
学科分类号
摘要
The model interpretability refers to the ability to express the real system behavior in an understandable way. With the increasing of reliability requirements in engineering practice, establishing a reliable and interpretable model to enhance human understanding of real systems has become one of the main objectives. Rule-based modeling approach can describe the system mechanism more intuitively. It can not only effectively integrate quantitative information and qualitative knowledge, but can also deal with uncertain information flexibly. This paper combs researches on the interpretability of rule-based modeling approach around the knowledge base, inference engine and model optimization, and finally makes a brief review and prospect. Copyright © 2021 Acta Automatica Sinica. All rights reserved.
引用
收藏
页码:1201 / 1216
页数:15
相关论文
共 126 条
  • [41] Bikdash M., A highly interpretable form of Sugeno inference systems, IEEE Transactions on Fuzzy Systems, 7, 6, pp. 686-696, (1999)
  • [42] Zhou Zhi-Jie, Chen Yu-Wang, Hu Chang-Hua, Zhang Bang-Cheng, Chang Lei-Lei, Evidential Reasoning, Belief Rule Base and Complex System Modeling, (2017)
  • [43] Yang J B, Sen P., A general multi-level evaluation process for hybrid MADM with uncertainty, IEEE Transactions on Systems, Man, and Cybernetics, 24, 10, pp. 1458-1473, (1994)
  • [44] Yang J B, Singh M G., An evidential reasoning approach for multiple-attribute decision making with uncertainty, IEEE Transactions on Systems, Man, and Cybernetics, 24, 1, pp. 1-18, (1994)
  • [45] Yang J B, Liu J, Wang J, Sii H S, Wang H W., Belief rule-base inference methodology using the evidential reasoning approach-RIMER, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 36, 2, pp. 266-285, (2006)
  • [46] Dempster A P., A generalization of Bayesian inference, Journal of the Royal Statistical Society. Series B: Methodological, 30, 2, pp. 205-247, (1968)
  • [47] Shafer G., A Mathematical Theory of Evidence, (1976)
  • [48] Poulton E C., Behavioral Decision Theory, (1994)
  • [49] Goodman I R, Nguyen HT., Uncertainty Models for Knowledge Based Systems, (1991)
  • [50] Liu J, Yang J B, Wang J, Sii H S, Wang Y M., Fuzzy rule-based evidential reasoning approach for safety analysis, International Journal of General Systems, 33, 2-3, pp. 183-204, (2004)