• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.457-459
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• 2003

This paper considers the application of Fuzzy Logic to Smart Decision process of Smart Sensor system that interprets and response to the change of environmental parameters. The considered system consists of three sensors: temperature sensor, humidity sensor and pressure sensor. The smartness of system is constituted by the applying of Fuzzy Logic. The paper discusses the technical details of the application of Fuzzy Logic for making the system to be smarter.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.696-700
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• 1998

Fuzzy random variables with piecewise linear membership functions are introduced from a practical viewpoint. The estimation of the expected values of these fuzzy random variables is also discussed and statistical application is denonstratied by using a real data set.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.403-406
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• 1997

This paper presents a Petri net approach for the control and monitoring of discrete event system. The proposed model is fuzzy Petri nets based on the fuzzy logic with Petri nets and the hierarchy concept. Fuzzy Petri nets have been used to model the imprecise situations which can arise within automated manufacturing system, and also the hierarchy concept allow to handle the refinement of places and transition in Petri nets model. These will form the foundation of a simulator-tool with manipulation interface for application of fuzzy Petri nets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.8
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• pp.789-795
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• 1992

The generalized Neyman-Pearson lemma Is reformulated In the framework of the fuzzy set theory. Based on the result, we define the locally optimum fuzzy test and derive the locally optimum fuzzy test function. As a pratical application of the locally optimum fuzzy test, detection of weak deterministic signals corrupted by purely-adative noise Is considered, which Is an important problem In statistical signal processing. Comparisons between the locally optimum and the locally optimum fuzzy tests are also made.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.225-231
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• 1998

TSK fuzzy system can represent effectively the behavior of a complex nonlinear system with low number of rules with the desired accuracy and guarantee the stability of the closed loop system, while the interpretation of the rules is difficult due to the functional nature of the consequents. On the contrary, fuzzy controller with singleton consequents is understandable intuitively and adjustable the rules easily due to qualitative expression of the rules. Ideally, one would like to combine the positive identification properties of TSK fuzzy system with the advantages of fuzzy controller with singleton consequents. Therefore, this paper suggests a method transforming TSK fuzzy systems into fuzzy systems with singleton consequents, and shows its application designing a fuzzy controller with singleton consequents by using the TSK fuzzy system when the behavior of a nonlinear system is described with a singleton fuzzy model by human esper.

• Journal of applied mathematics & informatics
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• v.42 no.1
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• pp.123-137
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• 2024

In this paper, Power fuzzy graphs is newly introduced by allotting fuzzy values on power graphs in such a way that the newly added edges, has the edge membership values between a closed interval which depends on vertex membership values and the length of the added edges. Power fuzzy subgraphs and total power fuzzy graphs are newly defined with properties and some special cases. It is observed that every power fuzzy graph is a fuzzy graph but the converse need not be true. Edges that are incident to vertices with the least vertex membership values are retained in the least power fuzzy subgraph. Further, the application of these concepts in real life time has been presented and discussed using power fuzzy graph model.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.2
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• pp.40-45
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• 2005

This paper has presented an application of an optimum grinding conditions based on the fuzzy logic. Fuzzy logic can handle vague and uncertain knowledge, and presents a scheme for integrating data with various kinds of grinding data. Especially, this research is capable of determining the grinding conditions taking into account some fuzzy membership function represented for trapezoidal form such as hardness and surface roughness of workpiece, material tensile strength and elongation, and requirement of grinding method. Larsen's fuzzy production method utilizing the fuzzy production rule can be applied on the establishment of grinding conditions, and also the output value obtained by the center of gravity method can effectively utilize the optimum grinding conditions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.619-624
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• 1998

This paper presents a new clustering algorithm called FCM algorithm for the design of fuzzy controller. FCM is an extended version of FCM(Fuzzy c-Means) algorithm and can estimate the number of clusters automatically and give membership grades $u_{ik}$ suitable for making fuzzy control rules. This paper also shows an example of its application to the line pursuit control of a car.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.925-928
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• 1993

In this paper the caracteristics of the fuzzy flip-flop which was proposed as a fuzzy sequential circuit is firstly mentioned. Secondly the circuit construction of typical fuzzy flip-flip circuits using VHDL (Very high speed integrated circuit Hardware Description Language) compiler and simulator is presented. Finally the possibility of the application of the fuzzy sequential circuit will be mentioned.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.985-988
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• 1993

An alternative approach to the design of application-driven fuzzy systems is proposed. A broad class of fuzzy systems applications requires a certain fuzzy partition of the input space while it demands for simple numerical quantities. For this class, a dedicated fuzzy system archictecture is presented and a design strategy is proposed. Both the single-input/single-output and multi-input/multi-output cases are considered. Numerical analysis are complete illustrating several aspects of the proposed framework.