• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.5
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• pp.9-18
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• 1997

The petri net is a graphic model which is adaptable in modeling a complex concurrent parallel ssystem, and it is widely used in the fields of industrial enginering, computer science, electric engineeringand chemistry. Recently, the net is applied to the communication protocol, and extended to represent complex systems. There are several extended petri nets named as TPN (timed petri net), SPN (stochastic petri net), FPN(fuzzy petri net) and TFPN(timed fuzzy petri net). Accodingly, this SPN (stochastic petri net), FPN (fuzzy petri net) and TFPN(timed fuzzy petri net). Accodingly, this paper proposes an advanced communication protocol modeling method using the fuzzy value of the transition and firing delay time as the arguments of the function. The proposed method can produce clearer firing rules, and it is supposed to be used to design and analyse communication protocols in great effection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.71-76
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• 2023

In this paper, we propose a fuzzy U-Net, a fuzzy deep learning model that applies fuzzy logic to improve performance in image segmentation using deep learning. Fuzzy modules using fuzzy logic were combined with U-Net, a deep learning model that showed excellent performance in image segmentation, and various types of fuzzy modules were simulated. The fuzzy module of the proposed deep learning model learns intrinsic and complex rules between feature maps of images and corresponding segmentation results. To this end, the superiority of the proposed method was demonstrated by applying it to dental CBCT data. As a result of the simulation, it can be seen that the performance of the ADD-RELU fuzzy module structure of the model using the addition skip connection in the proposed fuzzy U-Net is 0.7928 for the test dataset and the best.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.12
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• pp.84-94
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• 1996

In this work, a fuzzy petri net model for modeling a general form of fuzzy production system which consists of chaining fuzzy production rules and so requires multistage reasoning process is presented. For the obtained fuzzy petri net model, the net will be transformed into some matrices, and also be systematically led to an algebraic form of a state equation. Since it is fond that the approximate reasoning process in fuzzy systems corresponds to the dynamic behavior of the fuzzy petri net, it is further shown that the multistage reasoning process can be carried out by executing the state equation.

• The Pure and Applied Mathematics
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• v.13 no.1 s.31
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• pp.47-69
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• 2006

In this paper, an idea of graded fuzzy net is introduced; its convergence is studied; Relations between g-net and g-filter are established in L-fuzzy setting.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.1-12
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• 2005

In general, other conventional researches propose the fuzzy Petri net-based fuzzy reasoning algorithms based on the exhaustive search algorithms. If it can allow the certainty factors representing in the fuzzy production rules to use as the heuristic information, then it can allow the reasoning of rule-based systems to perform fuzzy reasoning in more effective manner. This paper presents a fuzzy Petri net(FPN) model to represent the fuzzy production rules of a rule-based system. Based on the fuzzy Petri net model, a weighted fuzzy reasoning algorithm is proposed to Perform the fuzzy reasoning automatically, This algorithm is more effective and more intelligent reasoning than other reasoning methods because it can perform fuzzy reasoning using the certainty factors which are provided by domain experts as heuristic information

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.180-186
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• 1998

This paper deals with the application of fuzzy Petri net to control the line tracking mobile robot. Comparing with the Petri net and the fuzzy Petri net, the fuzzy Petri net model is more effective than the use of Petri net, so the line tracking mobile robot has a little shake and also has a little moving distance than one of using the Petri, And thus the mobile robot shows less energy consumption

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.282-287
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• 2002

In this paper, we introduce the degrees of fuzzy net-convergences in L-fuzzy topologies using complete MV-algebras. We investigate the relationships among the degrees of fuzzy convergent, fuzzy cluster and fuzzy adherent points. We study the properties of net-convergences.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.364-364
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• 2000

Timed Petri Net(TPN) is one of methods to model and to analyze Discrete Event Dynamic Systems(DEDSs) with real time values. It has two time values, earliest firing time ($\alpha$$_{i}$) and latest firing time ($\beta$$_{I}$) for the each transition. A transition of TPN is fired at arbitrary time of time interval ($\alpha$$_{I}$, $\beta$$_{i}$). Uncertainty of firing time gives difficulty to analyze and estimate a modeled system. In this paper, we proposed the Fuzzy Transition Timed Petri Net(FTTPN) with fuzzy theory to determine the optimal transition time (${\gamma}$$_{i}$). The transition firing time (${\gamma}$$_{i}$) of FTTPN is determined from fuzzy controller which is modeled with information of state transition. Each of the traffic signal controllers are modeled using the proposed method and timed petri net. And its Performance is evaluated by simulation of traffic signal controller. controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.291-296
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• 2006

In context-aware computing environment, some context is characterized by a single event, but many other contexts are determined by a sequence of events which happen with some timing constraints. Therefore context inference could be conducted by monitoring the sequence of event occurrence along with checking their conformance with timing constraints. Some context could be described with fuzzy concepts instead of concrete concepts. Multiple entities may interact with a service system in the context-aware environments, and thus the context inference mechanism should be equipped to handle multiple entities in the same situation. This paper proposes a context inference model which is based on the so-called fuzzy colored timed Petri net. The model represents and handles the sequential occurrence of some events along with involving timing constraints, deals with the multiple entities using the colored Petri net model, and employs the concept of fuzzy tokens to manage the fuzzy concepts.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1326-1329
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• 1993

This work presents a net-based structure to model approximate reasoning using fuzzy production rules, the Fuzzy Petri Net model. The Fuzzy Petri Net model is formally defined as a n-uple of elements. It allows for the representation of simple and complex forms of rules such as rules with conjunction in the antecedent and qualified rules. Parallel rules and conflicting rules can be modeled as well. We also developed an analysis method based on state equations and two fuzzy reasoning algorithms. Finally, the proposed method is applied to an example.