• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.27 no.3
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• pp.214-220
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• 2001

The clinical application of the three-dimensional radiographic technique had been limited to standard Broadbent-Bolton cephalometer with biplanar stereoradiography. We developed a new method for compensating the error of head position in ordinary non-biplanar cephalostat. It became to possible to use the three dimensional cephalogram commonly in clinical bases. 1. The method of methemetical compensation of head positioning error in non-biplanar condition was evaluated with dry skull. The error of the method of first and the second trial was $0.46{\pm}1.21$, $0.33{\pm}0.90mm$, which means the error of the head positioning correction in conventional cephalogram was within clinical acceptance. 2. The reproducibility of this system for clinical application was 0.54 mm ($-2.99{\sim}2.26mm$) which defines the absolute mean difference of the first and second trial. Compare to the The landmark identification error $1.2{\pm}1.6mm$, the error of the measurement was within the range of landmark identification error. The result indicates the adequate clinical accuracy of the computation of three-dimensional coordinates by compensation of the error of the head position in ordinary non-biplanar cephalostat.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.127-135
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• 1999

Multivarialbe Boiler-Turbine H_\infty Control System Genetic Algorithm Weighting Functions $W_1$(s), $W_2$(s), and design parameter $\gamma$ that are given by Glover-Doyle algorithm, to optimally follow the output of reference model. The first method to do this is that the gains of weighting functions $W_1$(s), $W_2$(s), and design parameter are optimized simultaneously by genetic algorithm with the tournament method that can search more diversely, in the search domain which guarantees the robust stability of system. And the second method is that not only by genetic algorithm with the roulette-wheel method that can search more fast, in that search domain. The boiler-turbine H_\infty control system designed by theabove second method has not only the robust stability to a modeling error but also the the better command tracking preformance than those of the H_\infty control system designed by trial-and-error method and the above first method. Also, this boiler-turbine H_\infty control system has the better performance than that of the LQG/LTR contro lsystem. The effectiveness of this boiler-turbineH_\infty control system is verified by computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.419-427
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• 2016

This paper proposes a design method of LCL-filter for a grid-connected three-phase inverter using a discontinuous PWM (DPWM) method. When using a DPWM method, many harmonic voltages are generated in the inverter output compared to a continuous PWM (CPWM) method. Therefore, an optimized grid-connected filter design is required for a DPWM method. The proposed design method provides generalized formula to design accurate LCL-filter without trial and error procedures. An inverter side inductance is designed by analyzing the current ripple injected to the grid. The Optimized parameters of LCL-filter can be designed by analyzing the total harmonic distortion (THD) and the ripple attenuation factor of the output current. The proposed LCL filter design method is demonstrated by simulation and experimental results.

• Structural Engineering and Mechanics
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• v.82 no.3
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• pp.271-282
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• 2022

The active learning surrogate model based on adaptive sampling strategy is increasingly popular in reliability analysis. However, most of the existing sampling strategies adopt the trial and error method to determine the size of the Monte Carlo (MC) candidate sample pool which satisfies the requirement of variation coefficient of failure probability. It will lead to a reduction in the calculation efficiency of reliability analysis. To avoid this defect, a new method for determining the optimal size of the MC candidate sample pool is proposed, and a new structural reliability analysis method combining polynomial chaos-based Kriging model (PC-Kriging) with adaptive sampling region is also proposed (PCK-ASR). Firstly, based on the lower limit of the confidence interval, a new method for estimating the optimal size of the MC candidate sample pool is proposed. Secondly, based on the upper limit of the confidence interval, an adaptive sampling region strategy similar to the radial centralized sampling method is developed. Then, the k-means++ clustering technique and the learning function LIF are used to complete the adaptive design of experiments (DoE). Finally, the effectiveness and accuracy of the PCK-ASR method are verified by three numerical examples and one practical engineering example.

• Journal of Korean Society of Rural Planning
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• v.10 no.3 s.24
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• pp.41-51
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• 2004

This study aims to develop a potential evaluation method for urban spatial expansion using remote sensing (RS) and geographic information system (GIS). A multi-criteria evaluation method with several criteria and their weighting values was introduced to evaluate the score and quantification of the potential surface around the existing cities. The six criteria with one geographic factor, slope, and five accessibility factors, time distance from center of the city, national road, interchange of expressway, a big city, and station, were defined for the potential. RS techniques were applied for classification of the actual urban expansion maps between two periods, and GIS functions were used for score of accessibility criteria with a distance decay function from geographic, road and several point maps, which was developed in this study. The new methodology was applied to a test area, Suwon, between 1986 and 1996. In order to optimize the six weighting values, this study made new findings to search the optimal combination of the weighting values from new methodology, weighted scenario method for intensity order (WSM), combined with intensity order and AHP method, including a trial and error method for sensitivity analysis to make the intensity order. The optimal combination of the weighting values by the new method generated the optimal potential surface, considering spatial trend of urban expansion in the test area.

• Journal of Korean Association for Spatial Structures
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• v.10 no.4
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• pp.59-66
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• 2010

This study presents the topology optimization technique by density method to determine the initial shape of space truss structures. Most initial shape design is performed by designer's previous experiences and trial and error method instead of the application of reasonable optimization method. Thus, the reasonable and economical optimization methods are needed to be introduced for the initial shape design. Therefore, we set design domain for cantilever space truss structure as an example model. And topology optimization is used to obtain optimum layout for them, and then size optimization method is used to find the optimum member size. Therefore, the reasonable initial optimal shapes of spatial truss structures can be obtained through the topology and size optimization using density method.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.524-526
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• 1999

In the construction of successful fuzzy models and/or controllers for nonlinear systems, the identification of a good fuzzy inference system is an important yet difficult problem, which is traditionally accomplished by a time-consuming trial-and-error process. In this paper, we propose a systematic identification procedure for complex multi-input single-output nonlinear systems with DNA coding method. A DNA coding method is optimization algorithm based on biological DNA as conventional genetic algorithms(GAs) are. The strings in the DNA coding method are variable-length strings, while standard GAs work with a fixed-length coding scheme. the DNA coding method is well suited to learning because it allows a flexible representation of a fuzzy inference system. We also propose a new coding method fur applying the DNA coding method to the identification of fuzzy models. This coding scheme can effectively represent the zero-order Takagi-Sugeno(TS) fuzzy model. To acquire optimal TS fuzzy model with higher accuracy and economical size, we use the DNA coding method to optimize the parameters and the number of fuzzy inference system. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its application to a Duffing-forced oscillation system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.11
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• pp.990-996
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• 2008

Nowadays, the trend to a lightweight design accelerates the use of advanced high strength steel (AHSS) in automotive industry. Springback phenomena is a hot issue in the sheet metal forming, especially bending process using AHSS. Several analytical methods for that have been proposed in recent years. Each of method has their advantages and disadvantages. There are only a few optimal solutions which can minimize the two objectives simultaneously. In this study, an effective method optimized the multi objective value. The method by the design of experiments(DOE) and artificial neural network(ANN) was presented to compensate springback of bending parts. This method was applied to L and V bending process. The effective method could be optimized to multiple object. It was confirmed that the proposed method was more efficient than traditional manual FEA procedure and the trial and error approach for springback compensation.

• Journal of Mechanical Science and Technology
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• v.15 no.5
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• pp.580-591
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• 2001

This paper proposes a fuzzy-sliding mode control which is designed by a self tuning fuzzy inference method based on a genetic algorithm. Using the method, the number of inference rules and the shape of the membership functions of the proposed fuzzy-sliding mode control are optimized without the aid of an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. It is further guaranteed that the selected solution becomes the global optimal solution by optimizing Akaikes information criterion expressing the quality of the inference rules. In order to evaluate the learning performance of the proposed fuzzy-sliding mode control based on a genetic algorithm, a trajectory tracking simulation of the polishing robot is carried out. Simulation results show that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the trajectory control result is similar to the result of the fuzzy-sliding mode control which is selected through trial error by an expert. Therefore, a designer who does not have expert knowledge of robot systems can design the fuzzy-sliding mode controller using the proposed self tuning fuzzy inference method based on the genetic algorithm.

• Journal of Power Electronics
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• v.18 no.3
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• pp.723-735
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• 2018

Linear proportional-integral (PI) controllers are an attractive choice for controlling the speed of induction machines because of their simplicity and ease of implementation. Fractional-order PI (FO-PI) controllers, however, perform better than PI controllers because of their nonlinear nature and the underlying iso-damping property of fractional-order operators. In this work, an FO-PI controller based on the proposed first-order plus dead-time induction motor model and integer-order (IO) controllers, such as Ziegler-Nichols PI, Cohen-Coon PI, and a PI controller tuned via trial-and-error method, is designed. Simulation and experimental investigation on an indirect field-oriented induction motor drive system proves that the proposed FO-PI controller has better speed tracking, lesser settling time, better disturbance rejection, and lower speed tracking error compared with linear IO-PI controllers. Our experimental study also validates that the FO-PI controller maximizes the torque per ampere output of the induction machine and can effectively control the motor at low speed, in field-weakening regions, and under detuned conditions.