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

Type of Material: Thesis
Title: Studies On Some Classes Of Fuzzy Petri Net Models And Its Applications
Researcher: JAYASUDHA, S.
Guide: RAMANATHAN, K
Department: Department of Science and Humanities(Mathematics)
Publisher: Bharath University, Chennai
Place: Chennai
Year: 2017
Language: English
Subject: Arts and Humanities
Arts and Recreation
Humanities Multidisciplinary
Social Sciences
Arts, Humanities and Languages
Dissertation/Thesis Note: PhD; Department of Science and Humanities(Mathematics), Bharath University, Chennai, Chennai; 2017; D11SH002
Fulltext: Shodhganga

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035__|a(IN-AhILN)th_454890
040__|aBHAU_600073|dIN-AhILN
041__|aeng
100__|aJAYASUDHA, S.|eResearcher
110__|aDepartment of Science and Humanities(Mathematics)|bBharath University, Chennai|dChennai|ein|0U-0446
245__|aStudies On Some Classes Of Fuzzy Petri Net Models And Its Applications
260__|aChennai|bBharath University, Chennai|c2017
300__|dDVD
502__|bPhD|cDepartment of Science and Humanities(Mathematics), Bharath University, Chennai, Chennai|d2017|oD11SH002
520__|aPetri 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 dia
650__|aSocial Sciences|2UGC
650__|aArts, Humanities and Languages|2AIU
653__|aArts and Humanities
653__|aArts and Recreation
653__|aHumanities Multidisciplinary
700__|aRAMANATHAN, K|eGuide
856__|uhttp://shodhganga.inflibnet.ac.in/handle/10603/324567|yShodhganga
905__|afromsg

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