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Fuzzy Petri Nets of Education. J aroslav Knybel – Univesity of Ostrava. Necessity of Simulation. creation of new study programs optional and selection courses orientation of students Student input informa tion recommended way of passing the studies. Fuzzy Petri Nets.
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Fuzzy Petri Nets of Education Jaroslav Knybel – Univesity of Ostrava
Necessity of Simulation • creationof new study programs • optional and selection courses • orientation of students • Student • input information • recommended way of passing the studies University of Ostrava
Fuzzy Petri Nets • Graphicvisualization of simulation • Petri Nets • Open-endedinput information - „some“, „lot“, „small“, „middle“ Use Fuzzy University of Ostrava
Clasic Petri Nets • Place • Transition • Edge • Token University of Ostrava
Clasic Petri Nets Example – two processesandonejointsource University of Ostrava
Classical logic • Transition from one status to second one using IF THEN rules • Conjunction in antecedent • Disjunctionin antecedent University of Ostrava
Conjunction in antecedent • Let’s say that statement C is true only in case that statements A and B are true. Then transcript in Petri netsthe will be following µ(t):AB→C University of Ostrava
Disjuction in antecedent • Let’s say C is true when A or B is true. • Problem– this is a different net (token will be in A and B,so only one will get through) University of Ostrava
Petri netswith inhibitors • PN+inhibitive edge • E.g.: The transition will happen if it doesn’t contain token University of Ostrava
Logicin Petr netswith inhibitors • Conjunction in antecedent • Disjuctionin antecedent University of Ostrava
Fuzzy Petri net IF THEN rules • IF d1 THEN d2 - • IF d1 AND d2 THEN d3 - • IF d1 OR d2 THEN d3 - University of Ostrava
Model of transition through studies • Mandatory, optional, selective subjects • Variousorientations of studies • Initial knowledge of student • Required orientation of student • Volition of suitable subjects University of Ostrava
IF THEN rules • IF (p6) programming (at least) THEN (p7) subject „Basics of programming“ • IF (p0) programming (basics) AND (p1) object programming (at least) THENsubject „the Introduction into the object programming (p2)“ • IF Introduction into the object programming (good) OR Introduction into database systems (partly) THEN (p5) language UML • IF (p3) specialization of database (a lot) THEN (p4) subject Introduction into the database systems • IF Introduction into the database systems (well) THEN Relational database University of Ostrava
Graficalillustration University of Ostrava
Simulation • T0 = 0.84 • T1 = 0.89 • T2 = 0.71 • T3 = 0.97 • Let`s choose initial values P0, P1, P3, P6. • P0 = 0.71 • P1 = 0.58 • P3 = 0.92 • P6 = 0.58 • Output • P2 = 0.49 • P4 = 0.82 • P7 = 0.41 • P5 = 0.80 University of Ostrava
Simulators • Any independent software doesn’t exist for simulation of FPN. • CPN simulator – colourfulPetri nets (simulators where it is possible to set up property of statuses and even of transitions) University of Ostrava
Conclusion • Creation of simulator • Incorporation into the current systems • Extension of PN for Fuzzy modeling application University of Ostrava
The end Jaroslav Knybel – jaroslav.knybel@osu.cz