Studies On Some Classes Of Fuzzy Petri Net Models And Its Applications

Abstract

Petri net can be used to model properties such as process asynchronous events, concurrent operations, synchronization, and resource sharing, which may be used to characterize discrete event systems. Petri net can reveal the events which are triggered in the case of events that are active. These representations of events in both visual and mathematical way are helpful. If the events contain approximate and uncertain information then Fuzzy Petri net (FPN) are very useful in characterizing them using Fuzzy Logic. In another related aspects, Fuzzy Cognitive Maps (FCM) links goals, casual events and trends in a fuzzy feedback dynamical system. In this study, the following results are established in detail with adequate references, namely the results on comparison of some aspects of FPN and FCM, construction of an alert management systems by utilizing algorithm FPN based fuzzy rules, similar implementation of FIS (Fuzzy Inference System) in diabetes data using the tool MATLAB, generation of decision rules for diabetes data by data mining techniques and their representation by FPN. Moreover, comparative studies for classification performance by the tools WEKA and MATLAB are carried out. The nature of above research helps us to add socially significant results in our research direction. The huge gap between the mathematical concepts of Fuzzy Petri net and its applications is encouraged to be reduced by our research. newline