• 제목/요약/키워드: parameter function

검색결과 2,950건 처리시간 0.032초

가상현실을 이용한 건설공사 설계단계의 파라미터기반 3D객체 생성체계 구축방안 (Development of Parameter-based 3D Object Generation System by Using Virtual Reality for Construction Project Design Phase)

  • 강인석;권중희;문진석;문현석;지상복
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2008년도 정기 학술대회
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    • pp.108-113
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    • 2008
  • Virtual construction (VC) system enables project manager to visually check mistakes in design materials by using virtual reality technology. In using VC system, to make 3D object by each construction element is still tedious work. This study suggests an improved method to make 3D object by using parameter-based 3D generation function. The IDEFO model to organize the process for the function. A VC system by this function was developed in this study and the function was verified by a bridge project in this system.

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레이저 용접공정의 자동화를 위한 신경망 모델과 목적함수를 이용한 최적화 기법 개발 (Development of Optimization Methodology for Laser Welding Process Automation Using Neural Network Model and Objective Function)

  • 박영환
    • 한국공작기계학회논문집
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    • 제15권5호
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    • pp.123-130
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    • 2006
  • In manufacturing, process automation and parameter optimization are required in order to improve productivity. Especially in welding process, productivity and weldablity should be considered to determine the process parameter. In this paper, optimization methodology was proposed to determine the welding conditions using the objective function in terms of productivity and weldablity. In order to conduct this, welding experiments were carried out. Tensile test was performed to evaluate the weldability. Neural network model to estimate tensile strength using the laser power, welding speed, and wire feed rate was developed. Objective function was defined using the normalized tensile strength which represented the weldablilty and welding speed and wire feed rate which represented the productivity. The optimal welding parameters which maximized the objective function were determined.

공정변수의 변동을 고려한 손실함수를 통한 다중반응표면 최적화 (Multiresponse Optimization through a Loss Function Considering Process Parameter Fluctuation)

  • 권준범;이종석;이상호;전치혁;김광재
    • 대한산업공학회지
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    • 제31권2호
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    • pp.164-172
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    • 2005
  • A loss function approach to a multiresponse problem is considered, when process parameters are regarded as random variables. The variation of each response may be amplified through so called propagation of error (POE), which is defined as the standard deviation of the transmitted variability in the response as a function of process parameters. The forms of POE for each response and for a pair of responses are proposed and they are reflected in our loss function approach to determine the optimal condition. The proposed method is illustrated using a polymer case. The result is compared with the case where parameter fluctuation is not considered.

투과 단층촬영에서 공간가변 평활화를 사용한 경계보존 반복연산 재구성 (Edge-Preserving Iterative Reconstruction in Transmission Tomography Using Space-Variant Smoothing)

  • 정지은;;이수진
    • 대한의용생체공학회:의공학회지
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    • 제38권5호
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    • pp.219-226
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    • 2017
  • Penalized-likelihood (PL) reconstruction methods for transmission tomography are known to provide improved image quality for reduced dose level by efficiently smoothing out noise while preserving edges. Unfortunately, however, most of the edge-preserving penalty functions used in conventional PL methods contain at least one free parameter which controls the shape of a non-quadratic penalty function to adjust the sensitivity of edge preservation. In this work, to avoid difficulties in finding a proper value of the free parameter involved in a non-quadratic penalty function, we propose a new adaptive method of space-variant smoothing with a simple quadratic penalty function. In this method, the smoothing parameter is adaptively selected for each pixel location at each iteration by using the image roughness measured by a pixel-wise standard deviation image calculated from the previous iteration. The experimental results demonstrate that our new method not only preserves edges, but also suppresses noise well in monotonic regions without requiring additional processes to select free parameters that may otherwise be included in a non-quadratic penalty function.

저류함수법의 매개변수 추정: 1. 범용모형 개발 (Parameter Estimation of the Storage Function Model: 1. Development of the Universal Model for the Parameter Estimation)

  • 최종남;안원식;김형수;박민규
    • 한국방재학회 논문집
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    • 제10권6호
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    • pp.119-130
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    • 2010
  • 본 연구에서는 가상유역에 대한 분포형 모형의 적용을 통해 다양한 유역 및 유출조건에서도 적용 가능한 저류함수법의 매개변수를 추정하기 위한 범용모형을 개발하였다. 기존의 매개변수 추정식은 대부분 한정된 조건의 관측자료에 기초하고 있어 실제 유출에 영향을 미치는 인자를 민감하게 고려하기 힘든 문제점이 있었다. 약 35,000회의 다양한 조건을 고려한 유출모의 결과를 기초로 이를 가장 잘 반영해 줄 수 있는 매개변수 모형을 구성한 결과 저류함수법의 지체시간은 주로 유역내 가장 긴 유로의 특성과 밀접한 관련이 있고, 저류상수의 경우 유역의 특성들과 관련성이 높은 것으로 나타났다.

Variable Parameter Sliding Controller Design for Vehicle Brake with Wheel Slip

  • Liang, Hong;Chong, Kil-To
    • Journal of Mechanical Science and Technology
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    • 제20권11호
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    • pp.1801-1812
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    • 2006
  • In this paper, a 4-wheel vehicle model including the effects of tire slip was considered, along with variable parameter sliding control, pushrod force as the end control parameter, and an antilock sliding control, in order to improve the performance of the vehicle longitudinal response. The variable sliding parameter is made to be proportional to the square root of the pressure derivative at the wheel, in order to compensate for large pressure changes in the brake cylinder. A typical tire force-relative slip curve for dry road conditions was used to generate an analytical tire force-relative slip function, and an antilock sliding control process based on the analytical tire force-relative slip function was used. A retrofitted brake system, with the pushrod force as the end control parameter, was employed, and an average decay function was used to suppress the simulation oscillations. Simulation results indicate that the velocity and spacing errors were slightly larger than the results that without considering wheel slip effect, the spacing errors of the lead and follower were insensitive to the adhesion coefficient up to the critical wheel slip value, and the limit for the antilock control on non-constant adhesion road condition was determined by the minimum of the equivalent adhesion coefficient.

A DUAL ALGORITHM FOR MINIMAX PROBLEMS

  • HE SUXIANG
    • Journal of applied mathematics & informatics
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    • 제17권1_2_3호
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    • pp.401-418
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    • 2005
  • In this paper, a dual algorithm, based on a smoothing function of Bertsekas (1982), is established for solving unconstrained minimax problems. It is proven that a sequence of points, generated by solving a sequence of unconstrained minimizers of the smoothing function with changing parameter t, converges with Q-superlinear rate to a Kuhn-Thcker point locally under some mild conditions. The relationship between the condition number of the Hessian matrix of the smoothing function and the parameter is studied, which also validates the convergence theory. Finally the numerical results are reported to show the effectiveness of this algorithm.

THE CONVERGENCE OF A DUAL ALGORITHM FOR NONLINEAR PROGRAMMING

  • Zhang, Li-Wei;He, Su-Xiang
    • Journal of applied mathematics & informatics
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    • 제7권3호
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    • pp.719-738
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    • 2000
  • A dual algorithm based on the smooth function proposed by Polyak (1988) is constructed for solving nonlinear programming problems with inequality constraints. It generates a sequence of points converging locally to a Kuhn-Tucker point by solving an unconstrained minimizer of a smooth potential function with a parameter. We study the relationship between eigenvalues of the Hessian of this smooth potential function and the parameter, which is useful for analyzing the effectiveness of the dual algorithm.

전기자동차 배터리 모델링 및 파라미터 최적화 기법 연구 (The Research on the Modeling and Parameter Optimization of the EV Battery)

  • 김일송
    • 전력전자학회논문지
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    • 제25권3호
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    • pp.227-234
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    • 2020
  • This paper presents the methods for the modeling and parameter optimization of the electric vehicle battery. The state variables of the battery are defined, and the test methods for battery parameters are presented. The state-space equation, which consists of four state variables, and the output equation, which is a combination of to-be-determined parameters, are shown. The parameter optimization method is the key point of this study. The least square of the modeling error can be used as an initial value of the multivariable function. It is equivalent to find the minimum value of the error function to obtain optimal parameters from multivariable function. The SIMULINK model is presented, and the 10-hour full operational range test results are shown to verify the performance of the model. The modeling error for 25 degrees is approximately 1% for full operational ranges. The comments to enhance modeling accuracy are shown in the conclusion.

A Note on Admissibility and Finite Admissibility in Estimation

  • Byung Hwee Kim;Tae Ryoung Park
    • Communications for Statistical Applications and Methods
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    • 제1권1호
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    • pp.87-93
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    • 1994
  • Consider the problem of estimating the parameter of the model in which an observable random variable is represented by a unknown scalar parameter plus another random variable and the parameter, sample, and decision spaces consist of all integers. We first characterize the class of all admissible estimators and then characterize the class of all finitely admissible estimators. Finally, we show that two classes are identical.

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