• 제목/요약/키워드: Approximate function

검색결과 656건 처리시간 0.023초

SOBOLEV TYPE APPROXIMATION ORDER BY SCATTERED SHIFTS OF A RADIAL BASIS FUNCTION

  • Yoon, Jung-Ho
    • Journal of applied mathematics & informatics
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    • 제23권1_2호
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    • pp.435-443
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    • 2007
  • An important approach towards solving the scattered data problem is by using radial basis functions. However, for a large class of smooth basis functions such as Gaussians, the existing theories guarantee the interpolant to approximate well only for a very small class of very smooth approximate which is the so-called 'native' space. The approximands f need to be extremely smooth. Hence, the purpose of this paper is to study approximation by a scattered shifts of a radial basis functions. We provide error estimates on larger spaces, especially on the homogeneous Sobolev spaces.

다중 섬 유전자 알고리즘 기반 A60 급 격벽 관통 관의 방화설계에 대한 이산변수 근사최적화 (Approximate Optimization with Discrete Variables of Fire Resistance Design of A60 Class Bulkhead Penetration Piece Based on Multi-island Genetic Algorithm)

  • 박우창;송창용
    • 한국기계가공학회지
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    • 제20권6호
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    • pp.33-43
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    • 2021
  • A60 class bulkhead penetration piece is a fire resistance system installed on a bulkhead compartment to protect lives and to prevent flame diffusion in a fire accident on a ship and offshore plant. This study focuses on the approximate optimization of the fire resistance design of the A60 class bulkhead penetration piece using a multi-island genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class bulkhead penetration piece. For approximate optimization, the bulkhead penetration piece length, diameter, material type, and insulation density were considered discrete design variables; moreover, temperature, cost, and productivity were considered constraint functions. The approximate optimum design problem based on the meta-model was formulated by determining the discrete design variables by minimizing the weight of the A60 class bulkhead penetration piece subject to the constraint functions. The meta-models used for the approximate optimization were the Kriging model, response surface method, and radial basis function-based neural network. The results from the approximate optimization were compared to the actual results of the analysis to determine approximate accuracy. We conclude that the radial basis function-based neural network among the meta-models used in the approximate optimization generates the most accurate optimum design results for the fire resistance design of the A60 class bulkhead penetration piece.

CONTINUITY OF AN APPROXIMATE JORDAN MAPPING

  • Lee, Young-Whan
    • 대한수학회논문집
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    • 제20권3호
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    • pp.505-509
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    • 2005
  • We show that every $\varepsilon-approximate$ Jordan functional on a Banach algebra A is continuous. From this result we obtain that every $\varepsilon-approximate$ Jordan mapping from A into a continuous function space C(S) is continuous and it's norm less than or equal $1+\varepsilon$ where S is a compact Hausdorff space. This is a generalization of Jarosz's result [3, Proposition 5.5].

ON BOUNDEDNESS OF $\epsilon$-APPROXIMATE SOLUTION SET OF CONVEX OPTIMIZATION PROBLEMS

  • Kim, Gwi-Soo;Lee, Gue-Myung
    • Journal of applied mathematics & informatics
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    • 제26권1_2호
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    • pp.375-381
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    • 2008
  • Boundedness for the set of all the $\epsilon$-approximate solutions for convex optimization problems are considered. We give necessary and sufficient conditions for the sets of all the $\epsilon$-approximate solutions of a convex optimization problem involving finitely many convex functions and a convex semidefinite problem involving a linear matrix inequality to be bounded. Furthermore, we give examples illustrating our results for the boundedness.

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유연마니퓨레이터의 궤도최적화 (Trajectory Optimization of Flexible Manipulators)

  • 이승재;최연선;야마카와히로시
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2001년도 춘계학술대회논문집
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    • pp.979-983
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    • 2001
  • We develop a new method of simultaneous optimization of trajectory and shape of redundant flexible manipulators for collision-free utilizing the B-spline function and a mathematical programming method We adopt an approximate flexible manipulator model which consists of rigid bar elements and spring elements. We use B-spline function for determining the approximate trajectory and the expressions of the outline of obstacles. The used total performance index consists of 2 performance indices. The first is the driving energy, and the second is the trajectory deviation which is caused by the approximate modeling for the flexible manipulator. We design optimal collision-free trajectory of flexible manipulators by searching optimum positions of the control points for B-spline approximation which minimize the performance index subject to constraint condition for collision-free. Some examinations through numerical examples show the effectiveness of the method

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근사적 가중함수를 이용한 보강된 균열평판의 응력강도계수 계산에 대한 연구 (A study on the calculation of stress intensity factor for a patched crack using approximate weight function)

  • 김종호;이순복
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2000년도 추계학술대회논문집A
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    • pp.123-128
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    • 2000
  • A cracked-plate with a patch bonded on one side is treated with a crack-bridging model: assuming continuous distribution of springs acting between crack surfaces. the approximate weight function was introduced to obtain the stress intensity factor of patched crack subjected to residual stress or non-uniform stress. The stress intensity factors for the partially patched crack within finite plate or the patched crack initiated from a notch were successfully obtained by numerical calculation.

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근사 선탐색을 이용한 동적 반응 최적화 (Dynamic response optmization using approximate search)

  • 김민수;최동훈
    • 대한기계학회논문집A
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    • 제22권4호
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    • pp.811-825
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    • 1998
  • An approximate line search is presented for dynamic response optimization with Augmented Lagrange Multiplier(ALM) method. This study empolys the approximate a augmented Lagrangian, which can improve the efficiency of the ALM method, while maintaining the global convergence of the ALM method. Although the approximate augmented Lagragian is composed of only the linearized cost and constraint functions, the quality of this approximation should be good since an approximate penalty term is found to have almost second-order accuracy near the optimum. Typical unconstrained optimization algorithms such as quasi-Newton and conjugate gradient methods are directly used to find exact search directions and a golden section method followed by a cubic polynomial approximation is empolyed for approximate line search since the approximate augmented Lagrangian is a nonlinear function of design variable vector. The numberical performance of the proposed approach is investigated by solving three typical dynamic response optimization problems and comparing the results with those in the literature. This comparison shows that the suggested approach is robust and efficient.

A Kullback-Leibler divergence based comparison of approximate Bayesian estimations of ARMA models

  • Amin, Ayman A
    • Communications for Statistical Applications and Methods
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    • 제29권4호
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    • pp.471-486
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    • 2022
  • Autoregressive moving average (ARMA) models involve nonlinearity in the model coefficients because of unobserved lagged errors, which complicates the likelihood function and makes the posterior density analytically intractable. In order to overcome this problem of posterior analysis, some approximation methods have been proposed in literature. In this paper we first review the main analytic approximations proposed to approximate the posterior density of ARMA models to be analytically tractable, which include Newbold, Zellner-Reynolds, and Broemeling-Shaarawy approximations. We then use the Kullback-Leibler divergence to study the relation between these three analytic approximations and to measure the distance between their derived approximate posteriors for ARMA models. In addition, we evaluate the impact of the approximate posteriors distance in Bayesian estimates of mean and precision of the model coefficients by generating a large number of Monte Carlo simulations from the approximate posteriors. Simulation study results show that the approximate posteriors of Newbold and Zellner-Reynolds are very close to each other, and their estimates have higher precision compared to those of Broemeling-Shaarawy approximation. Same results are obtained from the application to real-world time series datasets.

기지국 위치 문제를 위한 목적함수의 최적해 및 근사해 (Optimal and Approximate Solutions of Object Functions for Base Station Location Problem)

  • 손석원
    • 정보처리학회논문지C
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    • 제14C권2호
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    • pp.179-184
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    • 2007
  • 이동 통신 시스템의 설계에 있어서 기지국의 위치를 선정하는 문제는 기본적으로 셀 내부 및 외부의 간접전파에 의한 최소 SIR을 만족하면서 최대한의 사용자를 최소의 기지국에 할당하는 문제로서 NP-hard 이다. 기존에 주로 사용된 목적함수는 창고위치문제에서 사용하던 것으로 CDMA 이동통신 시스템으로 직접 이용하는 단계에서 문제점이 발생한다. 그 문제점들을 해결하는 목적함수와 최적해 및 근사해를 구하는 알고리즘을 제안하고, 그에 따른 시뮬레이션을 하여 본 논문의 제안이 타당성이 있는지 평가 및 분석하였다. 본 논문에서는 기지국의 위치문제를 경험적 탐색방법을 사용하지 않고 혼합정수계획법의 완전해를 이용하여 최적해 및 근사해를 구하였다.

A Validation Method for Solution of Nonlinear Differential Equations: Construction of Exact Solutions Neighboring Approximate Solutions

  • Lee, Sang-Chul
    • International Journal of Aeronautical and Space Sciences
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    • 제3권2호
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    • pp.46-58
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    • 2002
  • An inverse method is introduced to construct benchmark problems for the numerical solution of initial value problems. Benchmark problems constructed through this method have a known exact solution, even though analytical solutions are generally not obtainable. The solution is constructed such that it lies near a given approximate numerical solution, and therefore the special case solution can be generated in a versatile and physically meaningful fashion and can serve as a benchmark problem to validate approximate solution methods. A smooth interpolation of the approximate solution is forced to exactly satisfy the differential equation by analytically deriving a small forcing function to absorb all of the errors in the interpolated approximate solution. A multi-variable orthogonal function expansion method and computer symbol manipulation are successfully used for this process. Using this special case exact solution, it is possible to directly investigate the relationship between global errors of a candidate numerical solution process and the associated tuning parameters for a given code and a given problem. Under the assumption that the original differential equation is well-posed with respect to the small perturbations, we thereby obtain valuable information about the optimal choice of the tuning parameters and the achievable accuracy of the numerical solution. Illustrative examples show the utility of this method not only for the ordinary differential equations (ODEs) but for the partial differential equations (PDEs).