• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.337-343
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• 2003

In this paper we present the prediction interval estimation method using bootstrap method for least squares support vector machine(LS-SVM) regression, which allows us to perform even nonlinear regression by constructing a linear regression function in a high dimensional feature space. The bootstrap method is applied to generate the bootstrap sample for estimation of the covariance of the regression parameters consisting of the optimal bias and Lagrange multipliers. Experimental results are then presented which indicate the performance of this algorithm.

• Nonlinear Functional Analysis and Applications
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• v.26 no.1
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• pp.65-70
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• 2021

We characterize the solution set for a second-order cone linear fractional optimization problem (P). We present sequential Lagrange multiplier characterizations of the solution set for the problem (P) in terms of sequential Lagrange multipliers of a known solution of (P).

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.10a
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• pp.40-44
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• 1997

The governing functional in plastic deformation has to satisfy the incompressible condition. This incompressible condition imposed on the velocity fields can be removed by introducing either the Langrange multiplier or the penalty function into the functional. In the study two-dimensional rigid plastic FEM programs using by Lagrange multiplier and penalty function are developed. A compression of cylinder and a spike forging are simulated to compare the data of loads, local mean stresses and reductions of volume.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.1
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• pp.59-63
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• 2005

In this article, we apply the standard method of Lagrange multipliers to examine the algorithm in a recent IEEE publication which calculates the optimal generation for minimizing the system loss using loss sensitivities derived by angle reference transposition, and show that the two algorithms are mathematically the same.

• The Pure and Applied Mathematics
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• v.19 no.2
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• pp.179-192
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• 2012

We find the solution minimizing the shortfall risk by using the Lagrange-multiplier method. The conventional duality method in the expected utility maximization problem is used and we get the same results as in the paper [21].

• Journal of the korean Society of Automotive Engineers
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• v.11 no.2
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• pp.24-33
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• 1989

본 고에서는 이러한 추세에 따라서, 보다 효율적인 optimization program에 대해서 소개하고자 한다. 사용한 최적화 알고리즘은 ALM(augmented lagrange multiplier) 방법을 적용해서 구속조건이 있는 문제를 구속조건이 없는 문제로 변환한 후, self-scaling BFGS(broydon-flecher-goldfarb-schanno)를 적용한다. BFGS의 각 descent 방향에서의 step 길이는, sequential search로 unimodal point를 구해서, golden section 방법으로 refine을 한후, cubic approximation을 적용해서 구한다.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.95-102
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• 2001

최적의 SVM 가중치를 선택하는 방법 중에서 메모리와 속도의 문제를 해결하는 방법 중 하나가 커널애더트론 방법(Kernel Adatron, KA)이다. 본 연구에서는 KA방법을 제곱무감각손실함수까지 확장을 한 알고리즘을 개발한다. 그리고 추정해야 될 라그랑제 배수(Lagrange multiplier)의 수를 반으로 줄이는 알고리즘을 제시한다. 그리고 제시된 알고리즘의 효율성을 여러 모의실험을 통해서 입증한다.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.475-484
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• 2004

This paper consider the testing problem of grouped heteroscedasticity in the linear regression model. We provide the Lagrange Multiplier(LM), Wald, Likelihood Ratio (LR) test statistis for testing of grouped heteroscedasticity. Monte Carlo experiments are conducted to study the performance of these tests.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.1
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• pp.50-59
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• 2014

In this paper, we develop an efficient approach to solve a multiple-item budget-constraint newsboy problem with a reservation policy. A conventional approach for solving such problem utilizes an approximation for the evaluation of an inverse of a Gaussian cumulative density function when the argument of the function is small, and a heuristic method for finding an optimal Lagrangian multiplier. In contrast to the conventional approach, this paper proposes more accurate method of evaluating the function by using the normalization and an effective numerical integration method. We also propose an efficient way to find an optimal Lagrangian multiplier by proving that the equation for the budget-constraint is in fact a monotonically increasing function in the Lagrangian multiplier. Numerical examples are tested to show the performance of the proposed approach with emphases on the behaviors of the inverse of a Gaussian cumulative density function and the Lagrangian multiplier. By using sensitivity analysis of different budget constraints, we show that the reservation policy indeed provides greater expected profit than the classical model of not having the reservation policy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1471-1488
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• 2018

Interference mitigation is a significant issue in the cognitive heterogeneous networks, this paper studied how to reduce the interference to macrocell users (MU) and improve system throughput. Establish the interference model with imperfect spectrum sensing by analyzing the source of interference complexity. Based on the user topology, the optimize problem was built to maximize the downlink throughput under given interference constraint and the total power constraint. We decompose the resource allocation problem into subcarrier allocation and power allocation. In the subcarrier assignment step, the allocated number of subcarriers satisfies the requirement of the femtocell users (FU).Then, we designed the power allocation algorithm based on the Lagrange multiplier method and the improved water filling method. Simulation results and performance analyses show that the proposed algorithm causes less interference to MU than the algorithm without considering imperfect spectrum sensing, and the system achieves better throughput performance.