• Title/Summary/Keyword: Descent

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Minimizing in Tracking Error Using Neural Network for Free-ranging Automated Guided Vehicle (신경회로망을 이용한 자율주행 반송차의 경로추종오차의 최소화)

  • 정인철;곽윤근;김수현;이두용;김동규
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.330-340
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    • 1998
  • 자율주행 반송차가 주어진 경로를 따라 주행 할 때 주행면의 불균일성과 같은 외란요인과 자율반송차 시스템 자체의 비선형성 등으로 인하여 원치 않는 경로추종오차가 발생하게 되는데 본 연구에서는 이러한 경로추종오차를 최소화하기 위해서 신경회로망을 이용한 경로추종 오차 보상방법을 제안한다. 본 방법에서는 신경회로망을 통하여 조향각 보상량을 제공하므로써 경로추종오차를 보상한다. 신경망은 다층 퍼셉트론을 채용하였으며 역전파 알고리즘의 최급강하규칙(Gradient descent rule)을 이용하여 학습을 수행하였다. 본 제안에서는 학습오차를 경로추종오차로부터 정의하므로써 경로추종오차가 최소화되록 신경회로망을 학습시켰다. 제안된 방법의 타당성은 다양한 경로에 대한 모의실험 및 실제 실험을 통하여 검증하였다.

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Numerical Solutio of Inverse Problem of Fuzzy Modeling with Pseudo First Order Approzimation

  • Ikoma, Norikazu;Hirota, Kaoru
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1230-1233
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    • 1993
  • Numerical solution of inverse problem of Takagi-Sugeno fuzzy model is proposed. The method is located on the application of numerical optimization to the fuzzy model. Steepest descent method is used for the numerical optimization. We use the linear approximation of fuzzy model, called pseudo first order approximation, by fixing the membership value on the neighborhood of the corresponding input. It is introduced in order to reduce the difficulty of optimization process. The efficiency of this method is shown by a numerical experiment.

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The Design of Predictive Controller for Chaotic Nonlinear Systems Using Wavelet Neural Networks (웨이블릿 신경 회로망을 이용한 혼돈 비선형 시스템에 대한 예측 제어기 설계)

  • 박상우;최종태;최윤호;박진배
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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    • pp.183-186
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    • 2002
  • In this paper, a predictive control method using wavelet neural network for chaotic nonlinear systems is presented. In our method, we use the adjusting method of the parameter for the training a wavelet neural network. The control signals are directly obtained by minimizing the difference between a reference signal and the output of a wavelet neural network. To verify the efficiency of our method, we apply it to the Duffing and the Henon system, which are a representative continuous and discrete time chaotic nonlinear system respectively.

Assessment of Optimization Methods for Design of Axial-Flow Fan (축류송풍기 설계를 위한 최적설계기법의 평가)

  • Choi, Jae-Ho;Kim, Kwang-Yong
    • 유체기계공업학회:학술대회논문집
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    • 1999.12a
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    • pp.221-226
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    • 1999
  • Three-dimensional flow analysis and numerical optimization methods are presented for the design of an axial-flow fan. Steady, Incompressible, three-dimensional Reynolds-averaged Wavier-Stokes equations are used as governing equations, and standard k-$\epsilon$ turbulence model is chosen as a turbulence model. Governing equations are discretized using finite volume method. Steepest descent method, conjugate gradient method and BFGS method are compared to determine the searching directions. Golden section method and quadratic fit-sectioning method are tested for one dimensional search. Objective function is defined as a ratio of generation rate of the turbulent kinetic energy to pressure head. Sweep angle distributions are used as design variables.

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Water Flowing and Shaking Optimization

  • Jung, Sung-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.2
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    • pp.173-180
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    • 2012
  • This paper proposes a novel optimization algorithm inspired by water flowing and shaking behaviors in a vessel. Water drops in our algorithm flow to the gradient descent direction and are sometimes shaken for getting out of local optimum areas when most water drops fall in local optimum areas. These flowing and shaking operations allow our algorithm to quickly approach to the global optimum without staying in local optimum areas. We experimented our algorithm with four function optimization problems and compared its results with those of particle swarm optimization. Experimental results showed that our algorithm is superior to the particle swarm optimization algorithm in terms of the speed and success ratio of finding the global optimum.

A Proposal of Descent Multi-point Search Method and Its Learning Algorithm for Optimum Value (최적치 계산을 위한 점감다점탐색법과 그 학습 알고리즘의 제안)

  • 김주홍;공휘식;이광직
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.17 no.8
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    • pp.846-855
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    • 1992
  • In this paper, the decrease multipoint search method and Its learning algorithm for optimum value computatlon method of object function Is proposed. Using this method, the number of evaluation point according to searching time can t)e reduced multipoint of the direct search method by applying the unlivarlate method. And the learning algorithm can reprat the same search method in a new established boundary by using the searched result. In order to Investigate the efficience of algorithm, this method this method is applied to Rosenbrock and Powell, Colvelle function that are Impossible or uncertain in traditional direct search method. And the result of application, the optimum value searching oil every function Is successful. Especially, the algorithm is certified as a good calculation method for producing global(absolute) optimum value.

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Application of Simulated Annealing and Tabu Search for Loss Minimization in Distribution Systems (베전 계통의 손실 최소화를 위한 시뮬레이티드 어닐링과 타부 탐색의 적용)

  • Jeon, Young-Jae;Kim, Jae-Chul
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.50 no.1
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    • pp.28-37
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    • 2001
  • This paper presents an efficient algorithm for the loss minimization of distribution system by automatic sectionalizing switch operation in large scale distribution systems. Simulated annealing is particularly well suited for large combinational optimization problem, but the use of this algorithm is also responsible for an excessive computation time requirement. Tabu search attempts to determine a better solution in the manner of a greatest-descent algorithm, but it can not give any guarantee for the convergence property. The hybrid algorithm of two methods with two tabu lists and the proposed perturbation mechanism is applied to improve the computation time and convergence property Numerical examples demonstrate the validity and effectiveness of the proposed methodology using a KEPCO's distribution system.

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A Fast Multiplier of Composite fields over finite fields (유한체의 합성체위에서의 고속 연산기)

  • Kim, Yong-Tae
    • The Journal of the Korea institute of electronic communication sciences
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    • v.6 no.3
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    • pp.389-395
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    • 2011
  • Since Elliptic Curve Cryptosystems(ECCs) support the same security as RSA cryptosystem and ElGamal cryptosystem with 1/6 size key, ECCs are the most efficient to smart cards, cellular phone and small-size computers restricted by high memory capacity and power of process. In this paper, we explicitly explain methods for finite fields operations used in ECC, and then construct some composite fields over finite fields which are secure under Weil's decent attack and maximize the speed of operations. Lastly, we propose a fast multiplier over our composite fields.

REPORT OF (CASE OF TAURDONTISM (TAURODONTISM의 증예보고)

  • Kim, Gyu-Taek
    • The Journal of the Korean dental association
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    • v.14 no.3
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    • pp.263-267
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    • 1976
  • The author detected rare taurodontisms shown in full mouth standard films of a 21-years-old male patient for the chief complaint of hypersensitivity caused by cervical area to cold and came to the folloeing conclusions through an asthropolpgical and geographic study. 1. Anomaly of this kind was also found ina korean, a mongoloid descent. 2. This study shaw that two cases of hypertaurodont molars and nine cases of hypotaurodont molars were found in one single patient. 3. No particular relationship was found between the occurrence of dental caries and the anomaly of this kind. 4. The genetical study on the case was out of the question because the family of the patient did not offer co-operation.

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Fuzzy Neural Network Based Generalized Predictive Control of Chaotic Nonlinear Systems (혼돈 비선형 시스템의 퍼지 신경 회로망 기반 일반형 예측 제어)

  • Park, Jong-Tae;Park, Yoon-Ho
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.2
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    • pp.65-75
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    • 2004
  • This paper presents a generalized predictive control method based on a fuzzy neural network(FNN) model, which uses the on-line multi-step prediction, fur the intelligent control of chaotic nonlinear systems whose mathematical models are unknown. In our design method, the parameters of both predictor and controller are tuned by a simple gradient descent scheme, and the weight parameters of FNN are determined adaptively during the operation of the system. In order to design a generalized predictive controller effectively, this paper describes computing procedure for each of the two important parameters. Also, we introduce a projection matrix to determine the control input, which deceases the control performance function very rapidly. Finally, in order to evaluate the performance of our controller, the proposed method is applied to the Doffing and Henon systems, which are two representative continuous-time and discrete-time chaotic nonlinear systems, res reactively.