Using fuzzy petri nets for static analysis of rule-bases

Abstract

We use a Fuzzy Petri Net (FPN) structure to represent knowledge and model the behavior in our intelligent object-oriented database environment, which integrates fuzzy, active and deductive rules with database objects. However, the behavior of a system can be unpredictable due to the rules triggering or untriggering each other (nontermination). Intermediate and final database states may also differ according to the order of rule executions (non-confluence). In order to foresee and solve problematic behavior patterns, we employ a static analysis on the FPN structure that provides easy checking of the termination property without requiring any extra construct. In addition, with our proposed fuzzy inference algorithm, we guarantee confluent rule executions. The techniques and solutions provided in this study can be utilized in various complex systems, such as weather forecasting applications and environmental information systems. © Springer-Verlag 2004.