• 제어로봇시스템학회논문지
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• 제12권7호
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• pp.631-636
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• 2006

In this paper, an algorithm of time series function forecasting using GMDH(group method of data handling) algorithm that gives more weight to the recent data is proposed. Traditional methods of GMDH forecasting gives same weights to the old and recent data, but by the point of view that the recent data is more important than the old data to forecast the future, an algorithm that makes the recent data contribute more to training is proposed for more accurate forecasting. The average error rate of electric power demand forecasting by the traditional GMDH algorithm which does not use data weighting algorithm is 0.9862 %, but as the result of applying the data weighting GMDH algorithm proposed in this paper to electric power forecasting demand the average error rate by the algorithm which uses data weighting algorithm and chooses the best data weighting rate is 0.688 %. Accordingly in forecasting the electric power demand by GMDH the proposed method can acquire the reduced error rate of 30.2 % compared to the traditional method.

• 한국정밀공학회지
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• 제29권9호
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• pp.986-994
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• 2012

This paper is concerned with the application of the vision control algorithm with weighting matrix in robot point placement task. The proposed vision control algorithm involves four models, which are the robot kinematic model, vision system model, the parameter estimation scheme and robot joint angle estimation scheme. This proposed algorithm is to make the robot move actively, even if relative position between camera and robot, and camera's focal length are unknown. The parameter estimation scheme and joint angle estimation scheme in this proposed algorithm have form of nonlinear equation. In particular, the joint angle estimation model includes several restrictive conditions. For this study, the weighting matrix which gave various weighting near the target was applied to the parameter estimation scheme. Then, this study is to investigate how this change of the weighting matrix will affect the presented vision control algorithm. Finally, the effect of the weighting matrix of robot vision control algorithm is demonstrated experimentally by performing the robot point placement.

• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.227-242
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• 2015

This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). In this paper, the torque ripple behavior is analyzed to validate the proposed weighting factor optimization method in the predictive control platform and shows the effectiveness of the system. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponds to minimum torque ripple and is compared with the results of conventional weighting factor based predictive control algorithm. The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. The conventional and introduced weighting factor optimization method in predictive control algorithm are validated through simulations and experimental validation in DS1104 R&D controller platform and show the potential control, tracking of variables with their respective references and consequently reduces the torque ripple.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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• pp.323-335
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• 1999

In this paper, we propose a new hybrid model of artificial neural networks(ANNs) and genetic algorithm (GA) to optimal feature transformation and feature weighting. Previous research proposed several variants of hybrid ANNs and GA models including feature weighting, feature subset selection and network structure optimization. Among the vast majority of these studies, however, ANNs did not learn the patterns of data well, because they employed GA for simple use. In this study, we incorporate GA in a simultaneous manner to improve the learning and generalization ability of ANNs. In this study, GA plays role to optimize feature weighting and feature transformation simultaneously. Globally optimized feature weighting overcome the well-known limitations of gradient descent algorithm and globally optimized feature transformation also reduce the dimensionality of the feature space and eliminate irrelevant factors in modeling ANNs. By this procedure, we can improve the performance and enhance the generalisability of ANNs.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.85.1-85
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• 2002

In this paper, a control strategy of position and force is proposed based on a switching algorithm. The main focus is the control of position and force in the same direction. The switching algorithm based on a fuzzy algorithm determines the weighting value of force control. First, the force control is dominant. If the position gets closer to the desire position, the weighting value of force control is closer to zero. The proposed algorithm is shown to be satisfactory to position and force control and the weighting factor is quite successful by simulation examples.

• Structural Engineering and Mechanics
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• 제1권1호
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• pp.119-135
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• 1993

The paper presents a generalized optimal active control algorithm for earthquake-resistant structures. The study included the weighting matrix configuration, stability, and time-delays for achieving control effectiveness and optimum solution. The sensitivity of various time-delays in the optimal solution is investigated for which the stability regions are determined. A simplified method for reducing the influence of time-delay on dynamic response is proposed. Numerical examples illustrate that the proposed optimal control algorithm is advantageous over others currently in vogue. Its feedback control law is independent of the time increment, and its weighting matrix can be flexibly selected and adjusted at any time during the operation of the control system. The examples also show that the weighting matrix based on pole placement approach is superior to other weighting matrix configurations for its self-adjustable control effectiveness. Using the time-delay correction method can significantly reduce the influence of time-delays on both structural response and required control force.

• Communications for Statistical Applications and Methods
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• 제17권1호
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• pp.17-27
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• 2010

분류분석에 사용되는 k-최근접이웃 분류기에 유전알고리즘을 적용하여 의미 있는 변수들과 이들에 대한 가중치 그리고 적절한 k를 동시에 선택하는 알고리즘을 제시하였다. 다양한 실제 자료에 대하여 기존의 여러 방법들과 교차타당성 방법을 통하여 비교한 결과 효과적인 것으로 나타났다.

• 대한전기학회논문지
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• 제37권10호
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• pp.727-732
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• 1988

In this paper, a parameter estimation method of linear systems with bounded output disturbances is studied. The bound of the disturbances is assumed to known Weighting factors are proposed to modify LS(Least Square) algorithm in the parameter estimation method. The conditions of weighting factors are given so that the estimation method has good convergence properties. This condition is more relaxed form than other known conditions. The compensation term in the estimation equations is represented by a function of the output prediction error and this function should lie in a specified region on x-y plane to satisfy these conditions of weighting factors. A set of weighting factor is selected and an algorithm is proposed using this set of weighting factor. The proposed algorithm is compared with another existing algorithm by simulation and its performance in parameter estimation id discussed.

• 한국멀티미디어학회논문지
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• 제14권5호
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• pp.650-657
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• 2011

본 논문은 매크로 블록 레벨에서 인간의 시각적인 특성을 고려한 새로운 H.264 스케일러블 확장을 위한 비트 할당 알고리즘을 제안한다. 제안된 알고리즘은 2 단계로 구성된다. 우선, 인간의 시각적인 특성에 기초한 관심영역을 중심으로, 각 매크로 블록에 대한 공간 주파수(spatial frequency)의 분석을 위한 시각적 가중치 모델을 제안한다. 두 번째 단계에서는, 제안된 모텔을 기초로 각각의 화질 계층에 존재하는 관심영역의 크기를 조절하여 주어진 비트 량에서, 최적의 비디오 화질을 얻기 위한 비트 할당 알고리즘을 제안한다. 실험을 통하여 제안된 알고리즘은 주관적 및 객관적 화질 평가에서 기존의 알고리즘보다 향상된 결과를 보여주었다.

• Nuclear Engineering and Technology
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• 제30권4호
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• pp.353-363
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• 1998

The H$_{\infty}$ algorithms of the mixed weight sensitivity is used for the robust design of the reactor power control system. The mixed weight sensitivity method requires the selection of the proper weighting functions for the loop shaping in frequency domain. The complexity of the system equation and the non-convexity of the problem make it very difficult to determine the weighting functions. The genetic algorithm which is improved and hybridized with the simulated annealing is applied to determine the weighting functions. This approach permits an automatic calculation and the resultant system shows good robustness and performance.