• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.945-948
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• 1993

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.543-545
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• 1999

In this paper, the composition method of global and local fuzzy reasoning concepts is researched for reducing the number of rules, not losing the performance for fuzzy controller. A new method is proposed in details that controls the interaction between global reasoning and local reasoning. In order to automatically acquire and optimize the method, the DNA coding algorithm is introduced to the local fuzzy reasoning of the proposed composition fuzzy reasoning method. The method is applied to the real liquid level control system for the purpose of evaluating the Performance. The simulation results show that the proposed technique can produce the fuzzy rules with higher accuracy and feasibility than the conventional methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1354-1357
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• 1993

This paper proposes that the best reasoning(i.e. rule evaluation) method which should be used in a fuzzy system significantly depends on the reasoning environment. It is shown that allowing for dynamic switching of reasoning methods leads to better performance, even when only two different reasoning methods are considered. This paper discusses DSFS (Dynamic Switching Fuzzy System) which dynamically switches and finds the best reasoning method (from among 80 different possible reasoning methods) to use depending on the reasoning situation. To overcome the reasoning speed and memory problem of DSFS due to its computational requirements, the DSFS Switching Reasoning Table method is proposed and its higher performance as compared to a conventional fuzzy system is shown. Finally, efforts to obtain general relationships between the characteristics of different reasoning methods and the actual control surface/environment is discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1058-1062
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• 1993

A fuzzy reasoning method is proposed for the implementation of control systems based on non-fuzzy microprocessors. The essence of the proposed method is to search the local active miles instead of the global rule base. Thus the reasoning is conveniently performed on a master cell as a fuzzy accelerating kernel, which is transformed from an active fuzzy cell. The interpolative reasoning is simplified via adopting the algebraic product of fulfillment for the conditional connective AND and the weighted average for the rule sentence connective ALSO.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1145-1150
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• 1993

In this paper, two methods of fuzzy modeling are prsented to describe the input-output relationship effectively based on relation characteristics utilizing simplified reasoning and neuro-fuzzy reasoning. The methods of modeling by the simplified reasoning and the neuro-fuzzy reasoning are used when the input-output relation of a system is 'crisp' and 'fuzzy', respectively. The structure and the parameter identification in the modeling method by the simplified reasoning are carried out by means of FCM clustering and the proposed GA hybrid scheme, respectively. The structure and the parameter identification in the modeling method by the neuro-fuzzy reasoning are carried out by means of GA and BP algorithm, respectively. The feasibility of the proposed methods are evaluated through simulation.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.92-100
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• 1995

Fuzzy reasoning has been applied to analysis of traffic problems on urban arterial road. As the analysis on factors of route choice has been already carried out, its result can be used for construction of the model. Route choice rate estimation by fuzzy reasoning was discussed from its structure and accuracy. The major objective of the study is to introduce some kinds of methods with fuzzy reasoning and to make their feature obvious. First, the production system model is introduced with consideration of reality to actual travel behavior. Second, overlapping areas of fuzzy language function are investigated. Finally, process of fuzzy reasoning was also considered. Five kinds of Fuzzy reasoning are compared to investigate in relation between shapes of membership function and estimation validity.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1285-1288
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• 1993

We tried gas identification by using one semiconductive gas sensor. As a method of gas identification, we used the fuzzy reasoning with fuzzy set of slope of gas pattern which is divided into arbitary interval. As a result, we got a good successful rate for hydrogen 66.6%, propane 79.1%, butane 100%, methane 100%, city gas 79.1% and alcohol 91.6%, respectively.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1999.11a
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• pp.240-246
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• 1999

This parer proposes fuzzy reasoning algorithm for improvement in Zonal Cavity Method that is difficult to calculate average illumination without lighting scope and reflection factor so on. This parer use fuzzy reasoning algorithm for maintainment of the best illumination in spite of some variation those are influenced of room illumination and cut down the difficult to be calculated used Zonal Cavity Method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.4
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• pp.56-67
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• 1999

In this paper, the new composition Irethod of global and local fuzzy reasoning concepts is proposed to reduce, optimize and automatically acquire the number of rules, without any lose of the general performances in conventional fuzzy controllers. In order to control the interaction between global reasoning and local reasoning, the DNA coding algorithm is introduced to the local fuzzy reasoning of the proposed composition fuzzy reasoning rrethod. The method is awlied to the real liquid level control system for the purpose of evaluating the performance. The sinru1ation results show that the proposed technique can control the system with higher accuracy and automatical1y acquire the fuzzy rules with rmre feasibility, than the conventional methods.ethods.