• Journal of Electrical Engineering and Technology
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• v.3 no.3
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• pp.320-330
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• 2008

This paper presents an improved dynamic programming (IDP) approach to solve the economic power dispatch problem including transmission losses in power systems. A detailed mathematical derivation of recursive dynamic programming approach for the economic power dispatch problem with transmission losses is presented. The transmission losses are augmented with the objective function using price factor. The generalized expression for optimal scheduling of thermal generating units derived in this article can be implemented for the solution of the economic power dispatch problem of a large-scale system. Six-unit, fifteen-unit, and forty-unit sample systems with non-linear characteristics of the generator, such as ramp-rate limits and prohibited operating zones are considered to illustrate the effectiveness of the proposed method. The proposed method results have been compared with the results of genetic algorithm and particle swarm optimization methods reported in the literature. Test results show that the proposed IDP approach can obtain a higher quality solution with better performance.

• Journal of the Korea Safety Management & Science
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• v.16 no.1
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• pp.213-220
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• 2014

This study suggests new approach to identify core technologies through patent analysis. Specially, the approach applied data mining technique and multi-criteria decision making method to the co-classification information of registered patents. First, technological interrelationship matrices of intensity, relatedness, and cross-impact perspectives are constructed with support, lift and confidence values calculated by conducting an association rule mining on the co-classification information of patent data. Second, the analytic network process is applied to the constructed technological interrelationship matrices in order to produce the importance values of technologies from each perspective. Finally, data envelopment analysis is employed to the derived importance values in order to identify priorities of technologies, putting three perspectives together. It is expected that suggested approach could help technology planners to formulate strategy and policy for technological innovation.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.182-186
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• 1997

This paper presents a mathematical approach to implementing distributed optimal power flow (OPF), wherein a regional decomposition technique is adopted to parallelize the OPF. Three mathematical decomposition coordination methods are introduced firs to implement the proposed distributed scheme: the Auxiliary Problem Principle (APP), the Predictor-Corrector Proximal Multiplier Method (PCPM), and the Alternating Direction Method (ADM). Then two alternative schemes for modeling distributed OPF are introduced; the Dummy Generator-Dummy Generator (DGDG) scheme and Dummy Generator-Dummy Load (DGDL) scheme. We present the mathematical analyses of the proposed approach, and demonstrate the approach on several test, systems, including IEEE Reliability Test Systems and parts of the ERCOT (Electric Reliability Council of Texas) system.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.449-460
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• 2007

Several fuzzy approaches can be considered for solving multi-objective transportation problem. This paper presents a fuzzy goal programming approach to determine an optimal compromise solution for the multiobjective transportation problem. We assume that each objective function has a fuzzy goal. Also we assign a special type of nonlinear (hyperbolic) membership function to each objective function to describe each fuzzy goal. The approach focuses on minimizing the negative deviation variables from 1 to obtain a compromise solution of the multiobjective transportation problem. We show that the proposed method and the fuzzy programming method are equivalent. In addition, the proposed approach can be applied to solve other multiobjective mathematical programming problems. A numerical example is given to illustrate the efficiency of the proposed approach.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.115-116
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• 2006

In these days, almost urban railway vehicle has been serviced under the random load application. But it is very important that fatigue lift prediction fur structures is major factor of safety. So do this, it is required that fatigue assessment method for cumulative damage approach while Korea domestic regulations only has endurance limit approach. With this endurance limit approach, fatigue lift prediction is impossible. In this research, it will be present that fatigue assessment for urban transit structure by using of cumulative damage approach method and related theories.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.24 no.2
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• pp.199-214
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• 2020

This paper describes the development of a parallel computational algorithm based on the finite element tearing and interconnecting (FETI) method that uses a local Lagrange multiplier. In this approach, structural computational domain is decomposed into non-overlapping sub-domains using local Lagrange multiplier. The local Lagrange multipliers are imposed at interconnecting nodes. 8-node solid element using extra shape function is adopted by using the representative volume element (RVE). The parallel computational algorithm is further established based on message passing interface (MPI). Finally, the present FETI-local approach is implemented on parallel hardware and shows improved performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.51-60
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• 2008

A solution method for fuzzy linear programs is proposed. A fuzzy linear program is converted to a crisp linear program with average indices being applied to the objective function and constraints. A comparative analysis between the proposed average index approach and the possibilistic approach is given. As an application example, the proposed method is applied to the linear programming model for fuzzy data envelopment analysis, and the result is compared with that of the possibilistic approach.

• International Journal of CAD/CAM
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• v.9 no.1
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• pp.31-36
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• 2010

3D point data acquired from laser scan or stereo vision can be quite noisy. A preprocessing step is often needed before a surface reconstruction algorithm can be applied. In this paper, we propose a nonparametric approach for noisy point data preprocessing. In particular, we proposed an anisotropic kernel based nonparametric density estimation method for outlier removal, and a hill-climbing line search approach for projecting data points onto the real surface boundary. Our approach is simple, robust and efficient. We demonstrate our method on both real and synthetic point datasets.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.143-146
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• 2004

In a situation that rank order information on attribute weights is captured, two solution approaches are presented. An exact solution approach via interaction with a decision-maker pursues progressive reduction of a set of non-dominated alternatives by narrowing down the feasible attribute weights set. In approximate solution approach, on the other hand, three categories of approximate methods such as surrogate weights method, the dominance value-based decision rules, and three classical decision rules are presented and their efficacies in terms of choice accuracy are evaluated via simulation analysis. The simulation results indicate that a method, which combines an exact solution approach through interactions with the decision-maker and the dominance value-based approach is recommendable in a case that a decision is not made at a single step under imprecisely assessed weights information.

• Korean Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.211-222
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• 1998

Parametric design is an important modeling paradigm in CAD/CAM applications, enabling efficient design modifications and variations. One of the major issues in parametric design is to develop a geometric constraint solver that can handle a large set of geometric configurations efficiently and robustly. In this appear, we propose a new approach to geometric constraint solving that employs a graph-based method to solve the ruler-and-compass constructible configurations and a numerical method to solve the ruler-and-compass non-constructible configurations, in a way that combines the advantages of both methods. The geometric constraint solving process consists of two phases: 1) planning phase and 2) execution phase. In the planning phase, a sequence of construction steps is generated by clustering the constrained geometric entities and reducing the constraint graph in sequence. in the execution phase, each construction step is evaluated to determine the geometric entities, using both approaches. By combining the advantages of the graph-based constructive approach with the universality of the numerical approach, the proposed approach can maximize the efficiency, robustness, and extensibility of geometric constraint solver.