• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2545-2547
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• 2000

In this paper, a hybrid fuzzy controller using genetic algorithm based on parameter estimation mode to obtain optimal control parameter is presented. First, The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PID's output in steady state by a fuzzy variable, namely, membership function of weighting coefficient. Second, genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller utilizing the conventional methods for finding PID parameters and estimation mode of scaling factor. The algorithms estimates automatically the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules according to the rate of change and limitation condition of control input. Computer simulations are conducted to evaluate the performance of proposed hybrid fuzzy controller. ITAE, overshoot and rising time are used as a performance index of controller.

• Journal of the Korean Statistical Society
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• 제28권3호
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• pp.347-358
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• 1999

Correspondence analysis is an exploratory method for two-way contingency tables intended to display the association pattern between row and column categories. It has been developed for several decades mainly in France and Japan and, nowadays, is popular worldwide. For the special case, however, that the column consists of ordered categories, correspondence analysis may yield ackward result so that it cannot be fully accommodated. That's because the row and column categories are assumed to be nominal in the ordinary correspondence analysis. The aim of this study is to develop the correspondence analysis for two-way contingency tables with ordered column categories. It is based on two specific algorithms,

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.438-441
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• 2004

In this study, we introduce a noble neurogenetic approach to the design of fuzzy controller. The design procedure dwells on the use of Computational Intelligence (CI), namely genetic algorithms and Fuzzy-Set based Neural Networks (FSNN). The crux of the design methodology is based on the selection and determination of optimal values of the scaling factors of the fuzzy controllers, which are essential to the entire optimization process. First, the tuning of the scaling factors of the fuzzy controller is carried out by using GAs, and then the development of a nonlinear mapping for the scaling factors is realized by using GA based FSNN. The developed approach is applied to a nonlinear system such as an inverted pendulum where we show the results of comprehensive numerical studies and carry out a detailed comparative analysis.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.897-899
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• 1999

This paper presents a scaling factor tuning method to improve the performance of fuzzy logic controller. Tuning rules and reasoning are utilized off-line to determine the scaling factors based on absolute value of the error and its difference. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a dc-servo motor control system. The performance of this control system is demonstrated higher than a conventional fuzzy logic controller(FLC).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.279-281
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• 2006

In this paper, we study an approach to design a self-tuning Fuzzy-PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of conversional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. The above problems are solved by adapting Fuzzy-PI controller for the fire angle control of rectifier.[7] The performance of the Fuzzy-PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain the optimal scaling factors of the Fuzzy-PI controller by Genetic Algorithms. In order to improve Fuzzy-PI controller, we adopt FIS to tune the scaling factors of the Fuzzy-PI controller on line. A comparative study has been performed between Fuzzy-PI and self-tuning Fuzzy-PI controller, to prove the superiority of the proposed scheme.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.404-406
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• 1998

In this paper, we propose a scaling factor tuning method to improve the performance of fuzzy controller. Tuning rules and reasoning are utilized on-line to determine the scaling factors based on absolute value of the error and its difference. A adaptive evolutionary computation (AEC) is used to search for the optimal tuning rules that will maximize the fitness function. Finally, the proposed fuzzy controller is applied to the angular stabilization of an inverted pendulum.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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• pp.213-217
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• 2008

본 논문에서는 표준 IMC-PID 제어기에 시스템 식별상의 위상 조절 인자를 설계 변수로 추가함으로 새로운 IMC-PID 제어기 설계 방법을 제안한다. 제안된 제어기의 동조법으로 해석적으로 구해진 주파수 영역 특성을 통해 주파수 영역 성능을 보장하도록 하는 설계 변수의 구속 조건 하에서 시간영역의 적분 오차 지표를 가격함수로 최소화하는 최적 해를 얻는다. 이 제안된 동조법은 다양한 설계 사양을 동시에 고려하도록 하여 기존의 IMC-PID의 단일 설계 변수 동조가 갖는 비유연성 문제를 개선하였다. 사례 연구에서 기존의 동조법들과의 성능 비교를 통해 그 유용성을 검토했다.

• 한국통신학회논문지
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• 제36권9B호
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• pp.1082-1091
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• 2011

DVFS (Dynamic Voltage and Frequency Scaling) 에 기초한 저전력 기법은 배터리를 사용하는 모바일 장치에서 동작시간 향상을 위하여 매우 중요하다. 본 연구에서는 DVFS기법에 기반을 둔 영상디코더의 에너지 소비를 최소화핸 스케줄링 알고리즘을 제안 한다 특히, 기존연구에서 간과된 디코더와 디스플레이 사이에 위치한 버퍼의 크기 제약을 모델에 포함하여 버퍼 넘침을 방지 하도록하며, 이 모델에서 수학적으로 에너지를 최소화하는 알고리즘을 제안하고 증명하였다. 실제 영상을 통한 시뮬레이션 결과 버퍼의 크기가 10 프레임정도에서 이득이 포화상태가 되며, 제안된 알고리즘이 기존의 직관적인 알고리즘들에 비하여 평균 10% 정도의 전력소모 절약을 얻을 수 있음을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권5호
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• pp.1554-1566
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• 2014

Cloud Computing allows application providers seamlessly scaling their services and enables users scaling their usage according to their needs. In this paper, using queuing game model, we present service scheduling schemes which are used in software as a service (SaaS). The object is maximizing the Cloud Computing platform's (CCP's) payoff via controlling the service requests whether to join or balk, and controlling the value of CCP's admission fee. Firstly, we treat the CCP as one virtual machine (VM) and analyze the optimal queue length with a fixed admission fee distribution. If the position number of a new service request is bigger than the optimal queue length, it balks. Otherwise, it joins in. Under this scheme, the CCP's payoff can be maximized. Secondly, we extend this achievement to the multiple VMs situation. A big difference between single VM and multiple VMs is that the latter one needs to decide which VM the service requests turn to for service. We use a corresponding algorithm solve it. Simulation results demonstrate the good performance of our schemes.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(1)
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• pp.157-160
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• 2000

In order to design a low complexity and high performance SOVA decoder for Turbo Codes, we need to analyze the decoding performance with respect to several important design parameters and find out optimal values for them. Thus, we use a scaling factor of soft output and a update depth as the parameters and analyze their effect on the BER performance of the SOVA decoder. finally, we shows the optimal values of them for maximum decoding performance of SOVA decoder for 3GPP complied Turbo codes.