• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 B
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• pp.705-707
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• 1997

An optimal tuning algorithm of scaling factors is presented in this paper to automatically improve the performance of fuzzy controller. Especially, fuzzy controller has determined an moderate Scaling factor through trial and error. The presented method estimates automatically the optimal values of I/O scaling factors, using modified steepest descent method and this optimal tuning is for nonlinear input/output scaling factors. Simulation results verify the validity of the presented method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.3004-3006
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• 2000

In this paper, we propose an optimal design method of Fuzzy-Neural Networks model with parallel structure for complex and nonlinear systems. The proposed model is consists of a multiple number of FNN connected in parallel. The proposed FNNs with parallel structure is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. We use a HCM clustering and GAs to identify the structure and the parameters of the proposed model. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model. we use the time series data for gas furnace and the numerical data of nonlinear function.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2473-2475
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• 2000

In this paper, we design a GA-fuzzy controller for position control and anti-swing at the destination point. Applied genetic algorithm is used to complement the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Lagrange equation is used to represent the motion equation of trolley and load in order to obtain mathematical modelling.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.215-220
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• 1998

In order to optimize fuzzy model, we use the optimal algorithm with a hybrid type in the identification of premise parameters and standard least square method in the identification of consequence parameters of a fuzzy model. The hybrid optimal identification algorithm is carried out using a genetic algorithm and improved complex method. Also, the performance index with weighting factor is proposed to achieve a balance between the insults of performance for the training and testing data. Several numerical examples are used to evaluate the performance of the proposed model.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(1)
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• pp.405-408
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• 2002

To support Internet traffic efficiently over ATM \networks, Guaranteed Frame Rate(GFR) has been proposed in tile ATM Forum to ensure minimum rate guarantees to VCs. In this paper, we proposed fuzzy logic based buffer management algorithm that provides MCR guarantee and fair sharing to GFR VCs. A key feature of proposed algorithm is its ability to accept or drop a new incoming packet dynamically based on buffer condition and load rate of VCs. This is achieved by using fuzzy logic controller for the production of a drop factor. Simulation result shows that proposed scheme significantly has improved fairness and TCP throughput compared with previous schemes.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.1021-1024
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• 2000

In this paper, a neuro-fuzzy system for quantitative characterization of chaotic signals is proposed. The proposed system is differ from the previous methods in that the nonlinear functions of the nonlinear dynamical systems are calculated as the invariant factor. In the proposed neuro-fuzzy system, the nonlinear functions are determined by supervised learning. From the reconstructed nonlinear functions, the proposed system can generate extrapolated chaotic signals. This feature will help the study of nonlinear dynamical systems which require large number of chaotic data. To confirm the validity of the proposed system, nonlinear functions are reconstructed from 1-dimensional and 2-dimensional chaotic signals.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1342-1345
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• 1993

In the cellular mobile communications as decreasing the cell radius to increse the reuse factor of frequencies, the handoff requests are increasing so that the efficient handoff decision making becomes a crucial problem. In this simulation study, we evaluate a set of handoff algorithms based on fuzzy-multicriteria decision making. These algorithms uses the parameters including the received signal strength intensity, the bit error rate and the distance between a mobile station and a base station. We compare the fuzzy algorithms in terms of call block ratio and handoff request ratio and call force ratio, and show the applicability of those algorithms in the cellular mobile communication systems.

• 정보처리학회논문지C
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• 제12C권2호
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• pp.229-234
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• 2005

본 논문에서는 ATM 네트워크에서 인터넷 트래픽 성능 향상을 위한 퍼지를 응용한 버퍼 관리 알고리즘을 제안한다. 제안된 알고리즘은 퍼지 제어기를 이용해서 새로 도착하는 패킷을 버퍼의 상태와 VC의 부하에 따라 동적으로 폐기를 결정하여 버퍼 이용 효율과 GFR의 요구사항을 충족할 수 있도록 하였다. 컴퓨터 시뮬레이션을 통해 기존의 버퍼 관리 알고리즘과 성능을 비교한 결과, 공평성과 TCP 수율 면에서 성능이 향상됨을 보였다.

• Industrial Engineering and Management Systems
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• 제7권1호
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• pp.34-43
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• 2008

In recent years, many electronics producing firms have looked upon total quality management (TQM) strategy as a means by which they could maintain competitive advantage. This empirical research evaluates TQM strategic factors in order to determine the critical success factors in environmental uncertainty. Fuzzy analytic hierarchy process (FAHP) is the proposed research methodology to discuss and tackle the different decision criteria like effective leadership, people management, customer focus, strategic plan and process management, being involved in identifying the TQM strategic critical success factors with uncertainty. The result shows that effective leadership is the most critical success factor in TQM strategy.

• Journal of Power Electronics
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• 제8권2호
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• pp.141-147
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• 2008

This paper deals with a new and improved control technique for shunt active filters (AF) used for compensating unwanted harmonic currents injected in the mains due to nonlinear varying loads. This work is motivated by the need to find a permanent solution to the rigorous hit and trial method for evaluating system parameters in an indirect control of AF. A fuzzy pre-compensated PI (Proportional-Integral) controller is used to fuzzify the reference DC voltage of AF to the controller input so that the overshoots and undershoots in its DC link voltage are minimized and the settling time is improved. A three-phase diode rectifier with R-L (Resistive-Inductive) load is used as a non-linear load to study the effectiveness of the proposed controller of the AF. Robustness to filter parameter variations, insensitivity to controller parameter variations, and transient response has been taken as performance evaluation parameters. The results are shown through simulations in Matlab using power system block sets to demonstrate the capability of the proposed controller of the AF.