Abstract
•A novel synergy-effect-incorporated fuzzy Petri net (SFPN) modeling paradigm is developed.•The transition enabling conditions and truth degree calculation rules incorporated with synergy effects are presented.•The proposed SFPN is capable of properly depicting the catalyst and inhibitor effects existing in fuzzy rule-based expert systems.•The advantages of the proposed SFPN are validated through a risk assessment case study.
As a graphical knowledge representation and reasoning tool, fuzzy Petri net (FPN) is widely used in risk assessment, fault diagnosis and many other fields. It can express the complex causal relationships among events and make fuzzy reasoning about them. In practical applications, there may be synergy effects among events, i.e., the occurrence of event a may increase or decrease the truth degree of event b. Traditional FPNs fail to express such effects, thus neglecting them during their reasoning procedure. To address this issue, this study proposes an FPN considering them for the first time. Firstly, this study illustrates the concept of synergy effects via practical application examples. Secondly, it develops the transition enabling conditions and truth degree calculation rules incorporated with synergy effects. Then, it formally defines a synergy-effect-incorporated fuzzy Petri net (SFPN). On this basis, it presents the production rules, transition firing rules and reasoning algorithm of SFPN to perform knowledge representation and reasoning for knowledge-based systems affected by synergy effects. Finally, it takes the risk assessment of equipment failure caused by corrosion as a running case to validate its feasibility and advantages.