Fuzzy Petri Net Representation and Reasoning Methods for Rule-Based Decision Making Systems
Summary :
In this paper, we propose a fuzzy Petri net model for a rule-based decision making system which contains uncertain conditions and vague rules. Using the transformation method introduced in the paper, one can obtain the fuzzy Petri net of the rule-based system. Since the fuzzy Petri net can be represented by some matrices, the algebraic form of a state equation of the fuzzy Petri net is systematically derived. Both forward and backward reasoning are performed by using the state equations. Since the proposed reasoning methods require only simple arithmetic operations under a parallel rule firing scheme, it is possible to perform real-time decision making with applications to control systems and diagnostic systems. The methodology presented is also applicable to classical (nonfuzzy) knowledge base systems if the nonfuzzy system is considered as a special case of a fuzzy system with truth values being equal to the extreme values only. Finally, an illustrative example of a rule-based decision making system is given for automobile engine diagnosis.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E76-A No.6 pp.974-983
- Publication Date
- 1993/06/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Concurrent Systems, Discrete Event Systems and Petri Nets
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Myung-Geun CHUN, Zeungnam BIEN, "Fuzzy Petri Net Representation and Reasoning Methods for Rule-Based Decision Making Systems" in IEICE TRANSACTIONS on Fundamentals,
vol. E76-A, no. 6, pp. 974-983, June 1993, doi: .
Abstract: In this paper, we propose a fuzzy Petri net model for a rule-based decision making system which contains uncertain conditions and vague rules. Using the transformation method introduced in the paper, one can obtain the fuzzy Petri net of the rule-based system. Since the fuzzy Petri net can be represented by some matrices, the algebraic form of a state equation of the fuzzy Petri net is systematically derived. Both forward and backward reasoning are performed by using the state equations. Since the proposed reasoning methods require only simple arithmetic operations under a parallel rule firing scheme, it is possible to perform real-time decision making with applications to control systems and diagnostic systems. The methodology presented is also applicable to classical (nonfuzzy) knowledge base systems if the nonfuzzy system is considered as a special case of a fuzzy system with truth values being equal to the extreme values only. Finally, an illustrative example of a rule-based decision making system is given for automobile engine diagnosis.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e76-a_6_974/_p
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@ARTICLE{e76-a_6_974,
author={Myung-Geun CHUN, Zeungnam BIEN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Fuzzy Petri Net Representation and Reasoning Methods for Rule-Based Decision Making Systems},
year={1993},
volume={E76-A},
number={6},
pages={974-983},
abstract={In this paper, we propose a fuzzy Petri net model for a rule-based decision making system which contains uncertain conditions and vague rules. Using the transformation method introduced in the paper, one can obtain the fuzzy Petri net of the rule-based system. Since the fuzzy Petri net can be represented by some matrices, the algebraic form of a state equation of the fuzzy Petri net is systematically derived. Both forward and backward reasoning are performed by using the state equations. Since the proposed reasoning methods require only simple arithmetic operations under a parallel rule firing scheme, it is possible to perform real-time decision making with applications to control systems and diagnostic systems. The methodology presented is also applicable to classical (nonfuzzy) knowledge base systems if the nonfuzzy system is considered as a special case of a fuzzy system with truth values being equal to the extreme values only. Finally, an illustrative example of a rule-based decision making system is given for automobile engine diagnosis.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - Fuzzy Petri Net Representation and Reasoning Methods for Rule-Based Decision Making Systems
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 974
EP - 983
AU - Myung-Geun CHUN
AU - Zeungnam BIEN
PY - 1993
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E76-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 1993
AB - In this paper, we propose a fuzzy Petri net model for a rule-based decision making system which contains uncertain conditions and vague rules. Using the transformation method introduced in the paper, one can obtain the fuzzy Petri net of the rule-based system. Since the fuzzy Petri net can be represented by some matrices, the algebraic form of a state equation of the fuzzy Petri net is systematically derived. Both forward and backward reasoning are performed by using the state equations. Since the proposed reasoning methods require only simple arithmetic operations under a parallel rule firing scheme, it is possible to perform real-time decision making with applications to control systems and diagnostic systems. The methodology presented is also applicable to classical (nonfuzzy) knowledge base systems if the nonfuzzy system is considered as a special case of a fuzzy system with truth values being equal to the extreme values only. Finally, an illustrative example of a rule-based decision making system is given for automobile engine diagnosis.
ER -
English
