• Journal of the Society of Naval Architects of Korea
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• v.46 no.4
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• pp.409-416
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• 2009

The structural design problems are acknowledged to be commonly multi-criteria in nature. The various multi-criteria optimization methods are reviewed and the most efficient and easy-to-use Pareto optimal solution methods are applied to structural optimization of a truss and a beam. The result of the study shows that Pareto optimal solution methods can easily be applied to structural optimization with multiple objectives, and the designer can have a choice from those Pareto optimal solutions to meet an appropriate design environment.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.213-220
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• 2004

Evolutionary algorithms are well-suited for multi-objective optimization problems involving several. often conflicting objective. Pareto-based evolutionary algorithms, in particular, have shown better performance than other multi-objective evolutionary algorithms in comparison. Recently, pareto-based evolutionary algorithms uses a density information in fitness assignment scheme for generating uniform distributed global pareto optimal front. However, the usage of density information is not Important elements in a whole evolution path but plays an auxiliary role in order to make uniform distribution. In this paper, we propose an evolutionary algorithms for multi-objective optimization which assigns the fitness using pareto dominance rank and density weighting, and thus pareto dominance rank and density have similar influence on the whole evolution path. Furthermore, the experimental results, which applied our method to the six multi-objective optimization problems, show that the proposed algorithms show more promising results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.701-706
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• 1998

A design method of rule -based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of " IF..., THEN,," statements. using the theories of optimization and linguistic fuzzy implication rules. The improved complex method, which is a powerful auto-tuning algorithm, is used for tuning of parameters of the premise membership functions in consideration of the overall structure of fuzzy rules. The optimized objective function, including the weighting factors, is auto-tuned for better performance of fuzzy model using training data and testing data. According to the adjustment of each weighting factor of training and testing data, we can construct the optimal fuzzy model from the objective function. The least square method is utilized for the identification of optimum consequence parameters. Gas furance and a sewage treatment proce s are used to evaluate the performance of the proposed rule-based fuzzy modeling.

• Journal of Information Management
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• v.42 no.2
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• pp.193-210
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• 2011

The study was applied to context window sizes and weighting method to obtain the best performance of word sense disambiguation using support vector machine. The context window sizes were used to a 3-word, sentence, 50-bytes, and document window around the targeted word. The weighting methods were used to Binary, Term Frequency(TF), TF ${\times}$ Inverse Document Frequency(IDF), and Log TF ${\times}$ IDF. As a result, the performance of 50-bytes in the context window size was best. The Binary weighting method showed the best performance.

• Korean Journal of Optics and Photonics
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• v.9 no.6
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• pp.417-422
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• 1998

In this paper we introduce a method to optimize panel parameters and drive signals in a matrix-adressed bistable twsited-nematic (BTN) liquid crystal display (LCD) panel. We measured the effect of data pulses on optical switching characteristics in a BTN LC cell to model the effect theoretically. We introduce a weighting function to model the effect of data pulses on the switching energy as a function of time. Once the weighting function is known, we can estimate the maximum number of lines for multiplexing operation at a given frame rate by calculating the minimum data pulse width. By characterizing a unit cell as we change panel parameters (for example, d/p ratio), we can optimize parameters for high-speed operation. We found that our theoretical predictions agree very well with experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.82-87
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• 1994

In this study, dynamic optimal design far a two degree-of-freedom anthropomorphic robot module is performed. Several dynamic design indices associated with the inertia matrix and the inertia power array are introduced. Analysis for the relationship between the dynamic parameters and the design indices shows that trade-offs exist between the isotropy and the dynamic design indices related to the actuator size. A composite design index is employed to deal with multi-criteria based design with different weighting factors, in a systematic manner. We demonstrate the fact that dynamic optimization is another significant step to enhance the system performances, followed by kinematic optimization.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.96-99
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• 2002

This paper proposes a method to select the overshoot design parameters of the LQ-PID controller by using convex optimization in order to satisfy the design specifications. The tuning parameters of LQ-PID controller are determinated by the relationships between the design parameter to control both the overshoot and the settling time and the weighting factors Q and R in LQR.

• Journal of the Optical Society of Korea
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• v.11 no.2
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• pp.55-58
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• 2007

We propose a systematic method for design of fiber-optic surface plasmon resonance (SPR) sensors. We used rigorous coupled wave analysis (RCWA) for analysis of the transmission spectrum, and the (1+1) evolution strategy (ES) was employed as an optimization tool. The simulation results show that the optimization method presented here is very useful in designing fiber-optic SPR sensor for strain and temperature measurement. This algorithm can be extended to another objective function with other weighting factors and optical parameters.

• The KSFM Journal of Fluid Machinery
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• v.16 no.2
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• pp.35-41
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• 2013

Inlet part of a printed circuit heat exchanger has been optimized by using three-dimensional Reynolds-Averaged Navier-Stokes analysis and surrogate modeling techniques. Kriging model has been used as the surrogate model. The objective function for the optimization has been defined as a linear combination of uniformity of mass flow rate and the pressure loss with a weighting factor. For the optimization, the angle of the inlet plenum wall, radius of curvature of the inlet plenum wall, and width of the inlet pipes have been selected as design variables. Twenty six design points are obtained by Latin Hypercube Sampling in design space. Through the optimization, considerable improvement in the objective function has been obtained in comparison with the reference design of PCHE.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.2 s.245
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• pp.128-134
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• 2006

Topology optimization is an effective scheme to obtain the initial design concept: however, it is hard to apply in case of non-linear or multi-objective problems. In this study, a modified topology optimization method is proposed to generate a structure of a swing arm type actuator satisfying maximum compliance as well. as maximum stiffness using the multi-objective optimization. approach. The multi-objective function is defined to maximize the compliance in the direction of focusing of the actuator and the second eigen-frequency of the structure. The design of experiments are performed and the response surface functions are formulated to construct the multi-objective function. The weighting factors between conflicting functions are determined by the back-error propagation neural network and the solution of multi-objective function is acquired using the genetic algorithm.