• 한국CDE학회논문집
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• 제21권4호
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• pp.443-452
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• 2016

This paper proposes a method for expensive black box optimization using radial basis functions (RBFs). The proposed algorithm is a computational strategy that uses a RBF model approximating the expensive black box function to predict an optimum. First, a RBF-based approximation technique is introduced and a sampling plan for estimation of the black box function is described. Then the proposed algorithm is explained, which presents the pseudo-codes for implementation and the detailed description of each step performed in the optimization process. In addition, numerical experiments will be given to analyze the performance of the proposed algorithm, by investigating computation accuracy, number of function evaluations, and convergence history. Finally, geometric distance problem as application example will be also presented for showing the algorithm applicability to different engineering problems.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.126-130
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• 2001

In this paper, we propose the design methodology of target tracking system using fuzzy basis function expansion (FBFE) based on virus evolutionary genetic algorithm(VEGA). In general, the objective of target tracking is to estimate the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical nonlinear filtering method such as extended Kalman filter (EKF), the performance of the system may be deteriorated in highly nonlinear situation. To resolve these problems of nonlinear filtering technique, by appling artificial intelligent technique to the tracking control of moving targets, we combine the advantages of both traditional and intelligent control technique. In the proposed method, after composing training datum from the parameters of extended Kalman filter, by combining FBFE, which has the strong ability for the approximation, with VEGA, which prevent GA from converging prematurely in the case of lack of genetic diversity of population, and by identifying the parameters and rule numbers of fuzzy basis function simultaneously, we can reduce the tracking error of EKF. Finally, the proposed method is applied to three dimensional tracking problem, and the simulation results shows that the tracking performance is improved by the proposed method.

• Journal of the Korean Data and Information Science Society
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• 제8권2호
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• pp.163-171
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• 1997

공학 분야에서 신경망에 대한 관심은 신호처리, 로보틱스, 컨트롤, 문자인식, 패턴인식 그리고 컴퓨터 그래픽 분야등에서 연구되고 있으며, 이들은 함수근사응용과 밀접한 관련이있다. 통계학 분야에서는 패턴인식의 판별분석, 주성분분석, 회귀분석 그리고 군집분석을 위한 신경망등에 대한 연구가 활발히 이루어지고 있다. 문자인식을 위한 다층 신경망을 학습시키기 위해 역전파 알고리즘이 널리 사용되고 있으나 이 알고리즘은 긴 훈련기간, 극소점 문제, 이상치(outlier)에 민감하다는 단점을 지니고 있다. 이상치에 민감한 일반적인 역전파 알고리즘의 단점을 극복하기 위해 이상치에 민감하지 않은 로버스트 알고리즘의 필요성이 대두되었다. 본 논문에서는 통계물리에서 자주 사용하는 방법을 이용하여 제안한 로버스트 역전파 알고리즘을 문자인식에 적용하여 일반적인 역전파 알고리즘의 문자인식 성능과 비교하였다.

• 대한토목학회논문집
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• 제9권1호
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• pp.33-40
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• 1989

철근 콘크리트 뼈대구조는 설계변수가 많고, 목적함수의 제약조건이 복잡하여 주로 반복적인 재해석에 의하여 최적해에 접근하는 방법이 사용되고 있다. 본 연구에서는 다단계분할(multilevel decomposition)에 의하여 최적화 문제를 형성하여 재해석과정을 줄이고 효과적으로 설계변수를 취할 수 있도록 하였다. 최적화의 단계는 첫째 단계에서 비선형거동에 의한 재분배모멘트의 설계공간을 계산하여 설계모멘트에 대한 제약조건식을 형성하고, 둘째 단계에서는 재분배 모멘트를 최적화하였으며, 셋째 단계에서는 설계단면을 최적화하였다. 이때 재분배 모멘트의 최적화에 따른 첫째 단계의 모멘트의 설계공간의 변화는 부재력 변화량 추정(force approximation technique)에 의하여 수정하도록 하며, 변수를 단계별로 줄여 수렴을 가속화시킬 수 있도록 하였다. 최적화 문제의 목적함수로는 경비함수를 취하였으며 영국 CP110의 한계상태설계법을 이용하여 부재의 응력제약조건식을 유도하고, 설계예를 통하여 본 연구의 타당성과 효율성을 구명하였다.

• 대한기계학회논문집
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• 제15권2호
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• pp.544-556
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• 1991

The optimization of many engineering design problems requires a nonlinear programming algorithm that is robust and efficient. A general-purpose nonlinear optimization program IDOL (Interactive Design Optimization Library) is developed based on the Augmented Lagrange Mulitiplier (ALM) method. The ideas of selecting a good initial design point, using resonable initial values for Lagrange multipliers, constraints scaling, descent vector restarting, and dynamic stopping criterion are employed for computational enhancement to the ALM method. A descent vector is determined by using the Broydon-Fletcher-Goldfarb-Shanno (BFGS) method. For line search, the Incremental-Search method is first used to find bounds on the solution, then the bounds are reduced by the Golden Section method, and finally a cubic polynomial approximation technique is applied to locate the next design point. Seven typical test problems are solved to show IDOL efficient and robust.

• 한국항해항만학회지
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• 제28권7호
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• pp.629-634
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• 2004

Continuous depth data are often required in applications of both onboard systems and maritime simulation. But data available are usually discrete and irregularly distributed. Based on the neuron network technique, methods of interpolation to the charted depth are suggested in this paper. Two algorithms based on Levenberg-Marquardt back-propaganda and radial-basis function networks are investigated respectively. A dynamic neuron network system is developed which satisfies both real time and mass processing applications. Using hyperbolic paraboloid and typical chart area, effectiveness of the algorithms is tested and error analysis presented. Special process in practical applications such as partition of lager areas, normalization and selection of depth contour data are also illustrated.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2004년도 Asia Navigation Conference
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• pp.37-44
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• 2004

Continuous depth data are often required in applications of both onboard systems and maritime simulation. But data available are usually discrete and irregularly distributed. Based on the neuron network technique, methods of interpolation to the charted depth are suggested in this paper. Two algorithms based on Levenberg-Marquardt back-propaganda and radial-basis function networks are investigated respectively. A dynamic neuron network system is developed which satisfies both real time and mass processing applications. Using hyperbolic paraboloid and typical chart area, effectiveness of the algorithms is tested and error analysis presented. Special process in practical applications such as partition of lager areas, normalization and selection of depth contour data are also illustrated.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.137-142
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• 2001

Since recent production system becomes that of the small quantity, large volume with high quality production, accurate and high speed inspection system is required. In such situation, noncontact 3D measurement system which utilized CCD cameras is useful technique in terms of system cost, speed of data acquisition, measuring accuracy and application. However, it has low accuracy compared with contact 3D measurement system because of the camera distortion, non uniformity of laser distribution and so on. For those reasons, in this paper precision enhancement method is studied considering radial camera distortion, and laser distribution. A distortion correction method is applied even to the standard lens. The laser slit beam trajectory is determined by 3 method: based of the Gaussian function signal approximation, the median method, the center of gravity method and the peak point of the Gaussian function method.

• Communications for Statistical Applications and Methods
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• 제31권3호
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• pp.337-347
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• 2024

Kernel density estimation is a prevalent technique employed for nonparametric density estimation, enabling direct estimation from the data itself. This estimation involves two crucial elements: selection of the kernel function and the determination of the appropriate bandwidth. The selection of the bandwidth plays an important role in kernel density estimation, which has been developed over the past decade. A range of methods is available for selecting the bandwidth, including the plug-in bandwidth. In this article, the proposed plug-in bandwidth is introduced, which leverages shifted Chebyshev series-based approximation to determine the optimal bandwidth. Through a simulation study, the performance of the suggested bandwidth is analyzed to reveal its favorable performance across a wide range of distributions and sample sizes compared to alternative bandwidths. The proposed bandwidth is also applied for kernel density estimation on real dataset. The outcomes obtained from the proposed bandwidth indicate a favorable selection. Hence, this article serves as motivation to explore additional plug-in bandwidths that rely on function approximations utilizing alternative series expansions.

• 한국항공우주학회지
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• 제33권3호
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• pp.39-46
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• 2005

본 논문에서는 광범위한 함수 근사성질을 갖고 있는 신경회로망을 이용하여, 시스템의 입출력 조화성분의 선형관계를 표현하기 위해 추정된 전달행렬의 적용범위를 확장할 수 있는 적응 고차조화제어(Higher Harmonic Control, HHC) 기법을 제안하고 있다. 신경회로망의 학습신호는 추정된 전달행렬을 기반으로 계산된 최적제어 이득 값 행렬을 이용하여 구성된다. 내부 안정성을 보장하기 위하여 신경회로망의 가중치 학습방법은 Lyapunov 직접 방법을 이용하여 유도하였다. 6개의 입력과 2개의 출력을 갖는 비선형 시스템에 대한 시뮬레이션 결과를 통해 적응 고차조화제어 기법이 불확실한 전달행렬에 적용 가능함을 보였다.