Fuzzy Petri Nets In Real-time Systems

In this thesis, we first study the basic Petri net (PN) and fuzzy Petri net (FPN) and introduce some related concepts and information. Then we briefly introduce some useful FPN-based fuzzy reasoning algorithms. In this area, we focus on pointing out an improved rule-based backward fuzzy reasoning algorithm which is fully discussed about in chapter 4 to analyze a model problem in detail. We get the same or even better results via our algorithm. In about recent twenty years, a large class of FPNs have come into being. But most of them are strongly related to a certain kind of practical problems and have some limitations such as high uncertaintys. We study some usual rules from the typical FPN models which have deep effects on the development of FPN itself.We point out a structure of weighted fuzzy Petri net (WFPN) and give the related rule-based fuzzy reasoning algorithm. We also point out an improved rule-based reasoning algorithm in order to improve the present algorithms and we give a kind of rule-based backward fuzzy reasoning algorithm. As for the examples, we compare the results obtained by using our algorithm with the existed results to make sure that our algorithm is practical and efficient. From the cited examples, the advantages of the improved algorithm are very obvious to be seen.Information engineering has become one of the stars in the area of computer engineering now. At the same time, FPNs are widely used in knowledge representation and artifical intelligence for its well according with the thinking way of human beings. There are now a great deal of wonderful works about applying FPN in production rule system of information engineering. Such performance break a new way in improving the parallel knowledge reasoning capability. And its efficiency is based on the strong knowledge representation ability of FPNs. In this thesis, we give the WFPN model for the application of FPN in this area.