• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.704-711
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• 1999

This paper presents a design of fuzzy power system stabilizer (FPSS) using adaptive evolutionary computation (AEC). We have proposed an adaptive evolutionary algorithm which uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations. FPSS shows better control performances than conventional power system stabilizer (CPSS) in three-phase fault with heavy load which is used when tuning FPSS. To show the robustness of the proposed FPSS, it is appliedto damp the low frequency oscillations caused by disturbances such as three-phase fault with normal and light load, the angle deviation of generator with normal and light load and the angle deviation of generator with heavy load. Proposed FPSS shows better robustness than CPSS.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.5
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• pp.66-70
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• 1997

This paper presents a parallel combinatorial variant of evolution strategy (PCES) to solve well-known combinatorial optimization problems, Quadratic assignment problems (QAPs). The PCES reduces the possibility of getting stuck in local minima due to maintenance of subpopulation and thus it is more effective than the CES. Experiment results on two benchmark problems show that the PCES is better than the cES and the genetic algorithm(GA).

• KIEE International Transactions on Electrophysics and Applications
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• v.4C no.6
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• pp.276-281
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• 2004

In this paper, the optimal design of a novel microstrip directional coupler with a grooved housing for high directivity characteristic is presented. It will be shown that the high directivity of the microstrip coupler can be achieved simply by attaching an optimized housing structure. over the microstrip, which is much easier to fabricate than other conventional types. The dimensions of the proposed structure are maximized by using (1+1) evolution strategy (ES) combined with the deterministic algorithm. To improve the effectiveness of the results, efficient optimization procedures suitable for the model are proposed. From these results, it is determined that the proposed structure indicates an improved directivity. The optimized results are verified by full wave analysis at the center frequency of 850MHz.

• KIEE International Transaction on Systems and Control
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• v.2D no.2
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• pp.53-58
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• 2002

In this paper, various aspects in magnetoencephalography (MEG) source localization are studied. To minimize the errors in experimental data, an approximation technique using a polynomial function is proposed. The simulation shows that the proposed technique yields more accurate results. To improve the convergence characteristics in the optimization algorithm, a hybrid algorithm of evolution strategy and sensitivity analysis is applied to the neuromagnetic inverse problem. The effectiveness of the hybrid algorithm is verified by comparison with conventional algorithms. In addition, an artificial neural network (ANN) is applied to find an initial source location quickly and accurately. The simulation indicates that the proposed technique yields more accurate results effectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.149-150
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• 2008

Generally, the propeller shaft rate (PSR) estimation algorithm for the classification of the sonar target has the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family from the frequency spectrum, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.408-410
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• 1994

This Paper Presents a learning strategy for neural networks based on genetic algorithms and evolution strategies. Genetic algorithms and evolution strategies are used to train weights of feedforward neural network to solve problems faster than neural network, especially backpropagation. Simulations are performed exclusive-OR problem, full-adder problem, sine function generator to demonstrate the effectiveness of neural-GA-ES.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.359-361
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• 1994

This paper propose a Neural - GA-ES DC motor speed controller. The purpose is to achieve accurate trajectory control of the motor speed. A feedforward neural network structure is used for the controller. Genetic algorithm and evolution strategy is used for learning controller. Simulations are performed to demonstrate the effectiveness of proposed genetic algorithm and evolution strategy with neural structure.

• Journal of the Korean Society for Railway
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• v.10 no.3 s.40
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• pp.306-312
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• 2007

This paper presents the optimal design method of the train repair facility based on the simulation analysis. The train is divided into the power car, motorized car and passenger car for the simulation process analysis and train repair facility is composed of each subsystems such as a blast, dry and wash workshop. In simulation analysis, we consider the critical (dependent) factors and design (independent) factors for the optimal design. Therefore, a simulation optimization uses Evolution Strategy (ES) in order to find the optimal design factors. Experimental results indicate that simulation design factors are sufficient to satisfy the conditions of dependent variables. The proposed analysis method demonstrates that simulation design factors determined by the simulation optimization are appropriate for real design factors in a real situation and the accuracy and confidence for the simulation results are increased.

• 한국정보통신설비학회:학술대회논문집
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• 2002.08a
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• pp.10-12
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• 2002

본 논문에서는 TEM Cell 의 최적 설계방법을 제안한다. 임피던스 부정합을 최소화 시키기 위해 Cell 내부의 특성 임피던스를 $50{\Omega}$으로 유지하며, 동시에 중심 도체판(Septum)의 길이와 도체판 날개(winglet)의 각을 변화 시킴으로써 내부 전자파의 균일도(Uniformity)를 최대로 하는 TEM Cell의 최적설계 방법을 제안하며 (1+1)ES를 적용하여 시험영역을 최대로 하는 최적 설계 변수들을 제시한다.

• Journal of the Optical Society of Korea
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• v.11 no.2
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• pp.55-58
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• 2007

We propose a systematic method for design of fiber-optic surface plasmon resonance (SPR) sensors. We used rigorous coupled wave analysis (RCWA) for analysis of the transmission spectrum, and the (1+1) evolution strategy (ES) was employed as an optimization tool. The simulation results show that the optimization method presented here is very useful in designing fiber-optic SPR sensor for strain and temperature measurement. This algorithm can be extended to another objective function with other weighting factors and optical parameters.