• Journal of the Korean Data and Information Science Society
• /
• 제26권2호
• /
• pp.517-524
• /
• 2015

Unlabeled examples are easier and less expensive to be obtained than labeled examples. In this paper semisupervised approach is used to utilize such examples in an effort to enhance the predictive performance of nonlinear quantile regression problems. We propose a semisupervised quantile regression method named semisupervised support vector quantile regression, which is based on support vector machine. A generalized approximate cross validation method is used to choose the hyper-parameters that affect the performance of estimator. The experimental results confirm the successful performance of the proposed S2SVQR.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 2002년도 가을 학술발표회 논문집
• /
• pp.271-278
• /
• 2002

Structural optimization using improved higer-order convex approximation is proposed in this paper. The proposed method is a generalization of the convex approximation method. The order of the approximation function for each constraint is automatically adjusted in the optimization process. And also the order of each design variable is differently adjusted. This self-adjusted capability makes the approximate constraint values conservative enough to maintain the optimum design point of the approximate problem in feasible region. The efficiency of proposed algorithm, compared with conventional algorithm is successfully demonstrated in the Three-bar Truss example.

• 한국전산구조공학회논문집
• /
• 제16권4호
• /
• pp.431-437
• /
• 2003

본 연구에서는 순차 설계영역 (SDD： sequential Design Domain) 개념을 사용한 GUI(Graphic User Interface)환경 프로그램을 개발하였다. 본 프로그램은 상용프로그램인 ANSYS와 최적설계 프로그램인 PLBA(Pshenichny-Lim-Belegundu-Arora)를 연결하고 비주얼 베이직을 이용하여 GUI환경에서 사용자가 초기값과 입력파일을 작성하고 결과를 확인할 수 있도록 하였다. 프로그램의 신뢰도를 검증하기 위해서 3부재 및 5부재 트러스 구조물을 수치예제로 선정하여 해석하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권4호
• /
• pp.2028-2041
• /
• 2019

Compressed sensing (CS) is a new theory. With regard to the sparse signal, an exact reconstruction can be obtained with sufficient CS measurements. Nevertheless, in practical applications, the transform coefficients of many signals usually have weak sparsity and suffer from a variety of noise disturbances. What's worse, most existing classical algorithms are not able to effectively solve this issue. So we proposed an efficient algorithm based on smoothed ${\ell}_0$ norm for sparse signal reconstruction. The direct ${\ell}_0$ norm problem is NP hard, but it is unrealistic to directly solve the ${\ell}_0$ norm problem for the reconstruction of the sparse signal. To select a suitable sequence of smoothed function and solve the ${\ell}_0$ norm optimization problem effectively, we come up with a generalized approximate function model as the objective function to calculate the original signal. The proposed model preserves sharper edges, which is better than any other existing norm based algorithm. As a result, following this model, extensive simulations show that the proposed algorithm is superior to the similar algorithms used for solving the same problem.

• 한국전자파학회논문지
• /
• 제22권2호
• /
• pp.191-198
• /
• 2011

본 논문에서는 1차원 모드 방정식의 FDTD 해석 결과와 분수 함수 근사법을 이용하여 다층 구조의 Green 함수를 근사화 하는 방법을 제안한다. 파수 값에 따른 FDTD 해석 결과를 Fourier 변환 과정을 거쳐 spectral domain 상에서 Green 함수를 계산한다. FDTD 수치 해석 결과로 얻은 Green 함수에 분수 함수 근사법을 적용하여 pole과 residue를 계산하여 Green 함수를 분수 함수로 근사화 한다. 제안된 방법은 path-loss 계산 방법 중 하나인 정상 모드(normal mode)에 사용할 수 있다. 단일 주파수 해석에 유효한 기존의 정상 모드 방법과는 달리 본 논문에서 제안하는 FDTD 기반 방법은 광대역 해석을 할 수 있다. 제안된 방법의 유용성을 입증하기 위해 정상 모드 해석기반의 Kraken 시뮬레이터 결과와 공진 모드의 pole 값을 비교한다. 또 알려진 해석해를 갖는 문제에 제안된방법을 적용하여 정확도를 검증하였다.

• 응용통계연구
• /
• 제10권2호
• /
• pp.353-366
• /
• 1997

본 논문에서는 주어진 손실함수에 대한 근사최적베이즈축차실험방법을 유도한다. 근사최적베이즈축차실험방법을 Pocock 실험방법, O'Brien and Fleming 실험방법과 ASN(average sample size) 함수와 베이즈 위험면에서 비교하기 위하여 몬테칼로(Monte-Carlo) 방법을 사용한다. 그룹축차실험방법에서 그룹 때문에 빚어지는 정보의 손실비율과 베이즈효율의 개념을 소개하고 여러 가지 다른 그룹 크기에 따른 정보의 손실을 측정한다.

• 한국전산응용수학회:학술대회논문집
• /
• 한국전산응용수학회 2003년도 KSCAM 학술발표회 프로그램 및 초록집
• /
• pp.4.2-4
• /
• 2003

In this paper, we describe how to approximate the solutions of partial differential equations by bicubic spline functions whose interpolation errors at non-grid points are smaller in general than those by linear interpolations of the original solution at grid points. We show that the bicubic spline function can be represented exactly or approximately by a fuzzy system, and that the resulting fuzzy rule table shows the contours of the solution function. Thus, the fuzzy rule table is identified as a digital image and the contours in the rule table provide approximate contours of the solution of partial differential equations. Several illustrative examples are included.

• 응용통계연구
• /
• 제22권6호
• /
• pp.1345-1353
• /
• 2009

We introduce a simple methodology, so-called generalized gamma-polynomial approximation, based on moment-matching technique to approximate survival and hazard functions in the context of parametric survival analysis. We use the generalized gamma-polynomial approximation to approximate the density and distribution functions of convolutions and finite mixtures of random variables, from which the approximated survival and hazard functions are obtained. This technique provides very accurate approximation to the target functions, in addition to their being computationally efficient and easy to implement. In addition, the generalized gamma-polynomial approximations are very stable in middle range of the target distributions, whereas saddlepoint approximations are often unstable in a neighborhood of the mean.

• 한국기계가공학회지
• /
• 제19권5호
• /
• pp.27-37
• /
• 2020

Structural optimization problems with discrete design variables require more function calculations (or finite element analyses) than those in the continuous design space. In this study, a method to find an optimal solution in the discrete design of the truss structure is presented, reducing the number of function calculations. Because a continuous optimal solution is the Karush-Kuhn-Tucker point that satisfies the optimality condition, it is assumed that the discrete optimal solution is around the continuous optimum. Then, response values such as weight, displacement, and stress are predicted using approximate models-referred to as hybrid metamodels-within specified design ranges. The discrete design method using the hybrid metamodels is used as a post-process of the continuous optimization process. Standard truss design problems of 10-bar, 25-bar, 15-bar, and 52-bar are solved to show the usefulness of this method. The results are compared with those of existing methods.

• Journal of the Korean Data and Information Science Society
• /
• 제25권2호
• /
• pp.431-438
• /
• 2014

Type I hybrid censoring scheme is the combination of the Type I and Type II censoring scheme introduced by Epstein (1954). Epstein considered a hybrid censoring sampling scheme in which the life testing experiment is terminated at a random time $T^*$ which is the time that happens rst among the following two; time of the kth unit is observed or time of the experiment length set in advance. The likelihood function of this scheme from the Rayleigh distribution cannot be solved in a explicit solution and thus we approximate the function by the Taylor series expansion. In this process, we propose four dierent methods of expansion skill.