• 대한산업공학회지
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• 제39권2호
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• pp.135-142
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• 2013

In B2B e-Marketplace for free gifts and goods, product-mix recommendation is provided frequently by analysing customer logs and/or performing collaborative and rules-based filtering. This study proposes a new process that encompasses the genetic algorithm and key working processes of B2B e-marketplace based on the previous cooperate client order data. Efficiency and accuracy of the proposed system have been confirmed by cross-confirmation of accumulated data in the e-marketplace. The system can provide better opportunities for manufactures and suppliers to select optimized product-mix without time consuming trials and errors in their B2B e-marketplace networks.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 1999년도 춘계종합학술대회
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• pp.355-360
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• 1999

본 논문에서는 퍼지 논리 제어기에서 전문가의 지식없이 시행 착오법에 의해 최적화 되지 않은 제어 규칙을 이용하는 경우에도, 소속 함수 관계와 스케일링 팩터를 유전자 알고리즘으로 최적화하여 우수한 제어 성능을 갖는 지능 제어 방식을 제안한다. 제안하는 제어 방식은 실제 플랜트는 퍼지 논리를 이용해서 제어를 하되 먼저 오프 라인상에서 퍼지 제어기의 소속 함수 초기 변수값과 스케일링 팩터의 초기값을 유전 알고리즘으로 최적화시킨후 제어를 하는 직접 적응 제어 방식이다. 제안된 제어 방식의 유용성을 확인하기 위하여 비선형 시스템을 제어 대상으로 기존의 퍼지 제어 방식과 시뮬레이션을 통하여 비교 및 검토를 한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.27-29
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• 2005

Using a generalized regression neural network, etch microtrenching was modeled. All neurons in the pattern layer were equipped with multi-factored spreads and their complex effects on the prediction performance were optimized by means of a genetic algorithm. For comparison, GRNN model was constructed in a conventional way. Comparison result revealed that GA-GRNN model was more accurate than GRNN model by about 30%. The microtrenching data were collected during the etching of silicon oxynitride film and the etch process was characterized by a statistical experimental design.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권2호
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• pp.121-126
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• 2006

In the recent years, the development of computer-controlled suspension dampers and actuators has improved the trade-off between the vehicle handling and ride comfort, and has led to the development of various damper control policies. The skyhook control is an effective control strategy for suppressing vehicle vibration. In this study, a fuzzy skyhook control is proposed and tuned by a genetic algorithm to improve ride comfort. The proposed fuzzy skyhook control is applied to a quarter-car model in order to compare its performance with continuous skyhook suspensions. To obtain optimized fuzzy skyhook control, scale factors and in-out membership functions are tuned by a genetic algorithm. The simulation results show that the fuzzy skyhook control offers more effective suspension performance over the continuous skyhook control.

• 한국군사과학기술학회지
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• 제20권2호
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• pp.272-278
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• 2017

In this paper, we consider a single-channel amplitude comparison monopulse system(SCACMS). The monopulse ratio curve(MR-C) of the SCACMS can be controlled by an amplitude difference between sum and different signal, a phase difference and the coefficient of the signal processor. We first propose the SCACMS with multiple variables, and then apply a genetic algorithm to optimize the multiple variables in terms of minimizing a root mean square error. The simulation results show that when three variables of the SCACMS are jointly optimized, the linear region of the MR-C can be extended approximately 187 % compared to that of two variables.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2006년도 전기학술대회논문집
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• pp.77-78
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• 2006

A mixed method between $H_2\;and\;H_{\infty}$ control are widely applied to systems which has parameter perturbation and uncertain model to obtain an optimal robust controller. Brushless Direct Current (BLDC) motors are widely used for high performance control applications. Conventional PID controller only provides satisfactory performance for set-point regulation. However, with the presence of nonlinearities, uncertainties and perturbations in the system, conventional PID is not sufficient to achieve an optimal robust controller. This paper presents an approach to ease designing a Mixed $H_2/H_{\infty}$ PID controller for controlling speed of Brushless DC motors and the genetic algorithm is used to solve the optimized problems. Numerical results are shown to prove that the performance in the proposed controller is better than that in the optimal PID controller using LQR approach.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.119-121
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• 1997

This paper suggests a design method of the robust model following PD control system using genetic algorithm. This PD control system is designed by applying genetic algorithm with reference model to the optimal determination of proportional and derivative gains that are given by PD servo controller. These proportional and derivative gains are optimized simultaneously in the search domain guaranteeing the robust stability of closed-loop system satisfying different stability margins. The effectiveness of this PD control system is verified by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.182-182
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• 2000

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that the selected solution become the global optimal solution by optimizing the Akaike's information criterion. The trajectory trucking experiment of the polishing robot system shows that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding model controller provides reliable tracking performance during the polishing process.

• 한국전자파학회논문지
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• 제11권4호
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• pp.642-648
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• 2000

유전자 앨거리즘을 이용하여 동축선 급전 원형 편파 사각 마이크로스트립 안테나를 설계하였다. 임피던스 및 유효 손실 탄젠트 그리고 축비 등을 포함하는 복잡한 목적 함수를 갖는 마이크로스트립 안테나 설계에 유전자 앨거리즘이 효과적임을 보였다. 패버티 마들로부터 입력 임피던스와 원형 편파의 축비를 유도하고, 안테나의 폭과 길이와 동축선 급전점을 유전자 앨거리즘을 이용하여 최적화 하였다. 설계된 안테나를 제작하고 시뮬레이션 결과와 비교하여 타당성을 검증하였다.

• Ocean Systems Engineering
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• 제5권2호
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• pp.91-107
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• 2015

Ship hull optimization is categorized as a bound, multi variable, multi objective problem with nonlinear constraints. In such analysis, where the objective function representing the performance of the ship generally requires computationally involved hydrodynamic interaction evaluation methods, the objective functions are not smooth. Hence, the evolutionary techniques to attain the optimum hull forms is considered as the most practical strategy. In this study, a parametric ship hull form represented by B-Spline curves is optimized for multiple performance criteria using Genetic Algorithm. The methodology applied to automate the hull form generation, selection of optimization solvers and hydrodynamic parameter calculation for objective function and constraint definition are discussed here.