• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.261-263
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• 2008

In power systems operation, state estimation takes an important role in security control. For the state estimation problem, the weighted least squares(WLS) method and the fast decoupled method have been widely used at present. But these algorithms have disadvantage of converging local optimal solution. In these days, a modern heuristic optimization method such as Particle Swarm Optimization(PSO), are introduced to overcome the problems of classical optimization. In this paper, we proposed particle swarm optimization (PSO) to search an optimal solution of state estimation in power systems. To demonstrate the usefulness of the proposed method, PSO algorithm was tested in the IEEE-57 bus systems. From the simulation results, we can find that the PSO algorithm is applicable for power system state estimation.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.513-518
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• 2011

In this paper, a unified design environment is developed for the optimization of electric machines based on continuum sensitivity. For electromagnetic (EM) system analysis, COMSOL scripting environment is used. Optimization module is developed by MATLAB programming, which can be combined with COMSOL script commands. The modules are combined into one MATLAB project, and iteration process necessary for the optimization of EM system can be performed efficiently. During the design process, visual feedback of the current design status is given to the designer. In addition, the B-Spline parametrization of the nodal points is implemented to obtain smooth boundary of the device. The developed software is applied to the problem of finding uniform flux density distribution at the air gap of an electromagnet to verify its feasibility and effectiveness.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.1-10
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• 2005

A new approach, Multi-Objective Design Exploration (MODE), is presented to address Multidisciplinary Design Optimization (MDO) problems by CFD-CSD coupling. MODE reveals the structure of the design space from the trade-off information and visualizes it as a panorama for Decision Maker. The present form of MODE consists of Kriging Model, Adaptive Range Multi Objective Genetic Algorithms, Analysis of Variance and Self-Organizing Map. The main emphasis of this approach is visual data mining. An MDO system using high fidelity simulation codes, Navier-Stokes solver and NASTRAN, has been developed and applied to a regional-jet wing design. Because the optimization system becomes very computationally expensive, only brief exploration of the design space has been performed. However, data mining result demonstrates that design knowledge can produce a good design even from the brief design exploration.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.2
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• pp.67-73
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• 2012

This paper proposes optimal maintenance strategies for power distribution systems that involve the use of the reliability-centered maintenance (RCM) method. We developed an improved decision model based on the Markov process. This model can obtain the optimal inspection interval and maintenance method based on the total expected cost. We used ordinal optimization for solving the optimal problem. Optimal maintenance strategies were presented by applying the developed method to the RBTS model. A B/C analysis proved that these strategies offer maximum benefit-to-cost.

• Journal of Mechanical Science and Technology
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• v.15 no.8
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• pp.1132-1142
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• 2001

The paper describes the construction of global function approximation models for use in design optimization via global search techniques such as genetic algorithms. Two different approximation methods referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the training data is not sufficiently provided or uncertain information may be included in design process. Fuzzy inference system is the central system for of identifying the input/output relationship in both methods. The paper introduces the general procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and presents their generalization capabilities in terms of a number of fuzzy rules and training data with application to a three-bar truss optimization.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.365-370
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• 2001

In order to minimize unstable flow occurred at a multiblade fan/scroll system, optimal angle and shape of cut-off was determined by using two-dimensional turbulent fluid field analyses and neural network. The results of CFD analyses were used for learning as data of input and output of neural network. After learning neural network optimization process was accomplished for design variables, the angle and the shape of cut-off, in the design domain. As a result of optimization, the optimal angle and shape were obtained as 71 and 0.092 times the outer diameter of impeller, respectively, which are very similar values to previous studies. Finally, it was verified that the fluid field is very stable for optimal angle and shape of cut-off by two-dimensional CFD analysis.

• Journal of Power System Engineering
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• v.15 no.6
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• pp.53-58
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• 2011

To optimization of mlod for fineblanking forming of sector gear of recliner, it was analyzed the effect of clearance, V-ring height, V-ring position, blank holding force and counter punch force. In case of 0.003 mm of clearancs, the finest shear plane was obtained, but optimization between die and punch clearance was 0.005 mm. The height of V-ring was 0.7 mm. In case of increasing of hold force, the size of shear plane got better and the decrement of thickness became smaller. Both the size of shear plane and the decrement of thickness increased according to increasing of counter punch force.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.514-523
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• 2002

Feeder arrangement is an important element of process planning for printed circuit board assembly systems. This paper newly proposes a feeder arrangement method for multihead-gantry chip mounters. The multihead-gantry chip mounters are very popular in printed circuit board assembly system, but the research has been mainly focused on single-head-gantry chip mounters. We present an integer programming formulation for optimization problem of multihead-gantry chip mounters, and propose a heuristic method to solve the large NP-complete problem in reasonable time. Dynamic programming method is then applied to feeder arrangement optimization to reduce the overall assembly time. Comparative simulation results are finally presented to verify the usefulness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5015-5027
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• 2015

Transceiver optimization in multiple input multiple output (MIMO) cognitive systems is studied in this paper. The joint transceiver beamformer design is introduced to minimize the transmit power at secondary base station (SBS) while simultaneously controlling the interference to primary users (PUs) and satisfying the secondary users (SUs) signal-to-interference-plus-noise ratio (SINR) based on the convex optimization method. Due to the limited cooperation between SBS and PUs, the channel state information (CSI) usually cannot be obtained perfectly at the SBS in cognitive system. In this study, both perfect and imperfect CSI scenarios are considered in the beamformer design, and the proposed method is robust to CSI error. Numerical results validate the effectiveness of the proposed algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.429-432
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• 2004

Multidisciplinary design optimization technique is applied to drum type washer in order to minimize the vibration of the cabinet. Dynamic analysis and structural analysis are carried out by using commercial programs to obtain the reliable responses. Analysis models are compared to the experimental responses and finally validated for further design. Two commercial programs are integrated by the design framework EMDIOS that provides interfaces to conveniently link between analyzers and performs design optimization. In this research we could obtain an optimum design that reduces the magnitude of amplitude by about 33% compared with the original design.