• 전기의세계
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• 제24권5호
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• pp.72-80
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• 1975

In this paper an application of the Monte Carlo method to optimum circuit design is discussed. T. Tsuda and T. Kiyono's algorithm based on the Monte Carlo method for solving multiple simul-taneous nonlinear equations is generalized to apply it to finding solutions of the constrained nonlinear optimization problem. The generalized algorithm derived here is directly applied to economical circuit design. In the cirsuit design, the object function is a cost function which is related to the cost of each circuit component. The constraint is the variance of the total system expressed by the variances of each circuit component. The design is to be determined so that the circuit has specified drift reliability with minimum cost. A practical example of economical circuit design and a general nonlinear function minimization is presented with food results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2486-2489
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• 2002

Pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.302-305
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• 1996

In this paper, an optimal identification method using fuzzy-neural networks is proposed for modeling of nonlinear complex systems. The proposed fuzzy-neural modeling implements system structure and parameter identification using the intelligent schemes together with optimization theory, linguistic fuzzy implication rules, and neural networks(NNs) from input and output data of processes. Inference type for this fuzzy-neural modeling is presented as simplified inference. To obtain optimal model, the learning rates and momentum coefficients of fuzz-neural networks(FNNs) and parameters of membership function are tuned using genetic algorithm(GAs). For the purpose of its application to nonlinear processes, data for route choice of traffic problems and those for activated sludge process of sewage treatment system are used for the purpose of evaluating the performance of the proposed fuzzy-neural network modeling. The show that the proposed method can produce the intelligence model w th higher accuracy than other works achieved previously.

• East Asian mathematical journal
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• 제28권3호
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• pp.293-303
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• 2012

Sequential quadratic programming (SQP) has been one of the most important methods for solving nonlinear constrained optimization problems. Recently, filter method, proposed by Fletcher and Leyffer, has been extensively applied for its promising numerical results. In this paper, we present and study an active set SQP-filter algorithm for inequality constrained optimization. The active set technique reduces the size of quadratic programming (QP) subproblem. While by the filter method, there is no penalty parameter estimate. Moreover, Maratos effect can be overcome by filter technique. Global convergence property of the proposed algorithm are established under suitable conditions. Some numerical results are reported in this paper.

• 전기학회논문지P
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• 제57권2호
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• pp.115-120
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• 2008

The EKF(Extended Kalman filter) method which is the state estimation algorithm of nonlinear stochastic system depends on the initial error and the estimated states. Therefore, the divergence of the estimated state can be caused if the initial values of the estimated states are not chosen as approximate real state values. In this paper, the demerit of the existing EKF method is improved using the EKF algorithm transformated by STWS(Single Term Walsh Series). This method linearizes each sampling interval of continous-time system through the derivation of an algebraic iterative equation without discretizing continuous system by the characteristic of STWS, the convergence of the estimated states can be improved. The validity of the proposed method is checked through comparison with the existing EKF method in simulation.

• Journal of KIEE
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• 제10권1호
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• pp.7-15
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• 2000

Source separation is a statistical method, the goal of which is to separate the linear instantaneous mixtures of statistically independent sources without resorting to any prior knowledge. This paper addresses a source separation algorithm which is able to separate the mixtures of sub- and super-Gaussian sources. The nonlinear function in the proposed algorithm is derived from the generalized Gaussian distribution that is a set of distributions parameterized by a real positive number (Gaussian exponent). Based on the relationship between the kurtosis and the Gaussian exponent, we present a simple and efficient way of selecting proper nonlinear functions for source separation. Useful behavior of the proposed method is demonstrated by computer simulations.

• 전산구조공학
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• 제7권3호
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• pp.177-183
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• 1994

현수교의 기하학적 비선형거동을 해석할 수 있는 해석방법을 개발하고 해석을 실시하였다. 해석은 사하중하에서의 초기형상해석과 활하중하에서의 비선형해석의 2단계로 해석하는 알고리즘을 개발하였다. 선형해석 결과와 비선형해석결과를 비교할 때 기하학적인 비선형 효고가 매우 크므로 해석 및 설계시에 반드시 고려해야 함을 알 수 있다. 해석치와 측정치를 비교분석한 결과 새로운 알고리즘이 매우 유용함을 보여주고 있다.

• Steel and Composite Structures
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• 제7권5호
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• pp.355-376
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• 2007

The purpose of this study is to predict and investigate the time-dependent creep behavior of composite materials. For this, firstly the evaluation method for the modulus of elasticity of whole fiber and matrix is presented from the limited information on fiber volume fraction using the singular value decomposition method. Then, the effects of fiber volume fraction on modulus of elasticity of GFRP are verified. Also, as a creep model, the nonlinear curve fitting method based on the Marquardt algorithm is proposed. Using the existing Findley's power creep model and the proposed creep model, the effect of fiber volume fraction on the nonlinear creep behavior of composite materials is verified. Then, for the time-dependent analysis of a composite material subjected to uniaxial tension and simple shear loadings, a user-provided subroutine UMAT is developed to run within ABAQUS. Finally, the creep behavior of center loaded beam structure is investigated using the Hermitian beam elements with shear deformation effect and with time-dependent elastic and shear moduli.

• Structural Engineering and Mechanics
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• 제39권1호
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• pp.93-113
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• 2011

The explicit nonlinear dynamic relaxation method (DRM) is applied to the nonlinear geodesic shape finding analysis by introducing fictional tensioned 'strings' along the desired seams with a three or four-node membrane element. A number of results from the numerical example for the nonlinear geodesic shape finding and patterning analysis are obtained by the proposed method to demonstrate the accuracy and efficiency of the developed method. Therefore, the proposed geodesic shape finding algorithm may improve the applicability of a four-node membrane element to membrane structural engineering and design analysis simultaneously for the shape finding, stress, and patterning analysis.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 전력전자학술대회 논문집
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• pp.272-275
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• 2001

In this paper, author consider the nonlinear control by using feedback linearization for independent control and estimation algorithm such as speed, rotor flux and rotor resistance to achieve sensorless control of induction motor. The dynamic characteristics of the proposed nonlinear control algorithm is verified by simulation.