• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.21-27
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• 2015

An improved method based on direct extraction and simultaneous optimization is developed to determine model parameters of symmetric inductors fabricated by the high resistivity(HR) silicon-on-insulator(SOI) RF CMOS process. In order to improve modeling accuracy, several model parameters are directly extracted by Y and Z-parameter equations derived from two equivalent circuits of symmetric inductor and grounded center-tap one, and the number of unknown parameters is reduced using parallel resistance and total inductance equations. In order to improve optimization accuracy, two sets of measured S-parameters are simultaneously optimized while same model parameters in two equivalent circuits are set to common variables.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.263-269
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• 2006

An optimization model was developed for groundwater development and management in coastal areas. The optimization model consists of coastal groundwater flow model and optimization techniques. The objective of this work is to validate sharp-interface model which is one of major components of the optimization model. A laboratory experimental model is built to simulate freshwater lens, i.e., layer of freshwater floating on top of saltwater, phenomena. Experimental results for the position of fresh-saltwater sharp-interface and the salinity in well are compared with numerical results. Average ratio of relative error is estimated approximately between 2.91% and 4.39%. And the numerical results are in good agreement with the laboratory results of water quality in well in addition to the position of sharp-interface. Accordingly the evaluation of coastal groundwater flow using sharp-interface model can produce reasonable results.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.3
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• pp.3-13
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• 2005

The conceptual rainfall-runoff models are used to predict complex hydrological effects of a basin. However, to obtain reliable results, there are some difficulties and problems in choosing optimum model, calibrating, and verifying the chosen model suitable for hydrological characteristics of the basin. In this study, Genetic Algorithm and SCE-UA method as global optimization methods were applied to compare the each optimization technique and to analyze the application for the rainfall-runoff models. Modified TANK model that is used to calculate outflow for watershed management and reservoir operation etc. was optimized as a long term rainfall-runoff model. And storage-function model that is used to predict real-time flood using historical data was optimized as a short term rainfall-runoff model. The optimized models were applied to simulate runoff on Pyeongchang-river watershed and Bocheong-stream watershed in 2001 and 2002. In the historical data study, the Genetic Algorithm and the SCE-UA method showed consistently good results considering statistical values compared with observed data.

• Journal of Wetlands Research
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• v.21 no.1
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• pp.1-8
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• 2019

In this study, the multi-objective optimization method is attemped to optimize the hydrological model to estimate the runoff through two hydrological processes. HL-RDHM, a distributed hydrological model that can simultaneously estimate the amount of snowfall and runoff, was used as the distributed hydrological model. The Durango River basin in Colorado, USA, was selected as the watershed. MOSCEM was used as a multi-objective optimization method and parameter calibration and hydrologic model optimization were tried by selecting 5 parameters related to snow melting and 13 parameters related to runoff. Data from 2004 to 2005 were used to optimize the model and verified using data from 2001 to 2004. By optimizing both the amount of snow and the amount of runoff, the RMSE error can be reduced from 7% to 40% of the simulation value based on the initial solution at three SNOTEL points based on the RMSE. The USGS observation point of the outflow is improved about 40%.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.9-17
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• 2006

This paper deals with a discrete simulation optimization method for designing a complex probabilistic discrete event simulation. The developed algorithm uses the configuration algorithm that can change decision variables and the stopping algorithm that can end simulation in order to satisfy the given objective value during single run. It tries to estimate an auto-regressive model for evaluating correctly the objective function obtained by a small amount of output data. We apply the proposed algorithm to M/M/s model, (s, S) inventory model, and known-function problem. The proposed algorithm can't always guarantee the optimal solution but the method gives an approximate feasible solution in a relatively short time period. We, therefore, show the proposed algorithm can be used as an initial feasible solution of existing optimization methods that need multiple simulation run to search an optimal solution.

• Journal of applied mathematics & informatics
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• v.26 no.1_2
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• pp.337-347
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• 2008

Based on social welfare maximum theory, the optimal scale of power plants entering generation power market being is researched. A static non-cooperative game model for short-term optimization of power plants with different cost is presented. And the equilibrium solutions and the total social welfare are obtained. According to principle of maximum social welfare selection, the optimization model is solved, optimal number of power plants entering the market is determined. The optimization results can not only increase the customer surplus and improve power production efficiency, but also sustain normal profits of power plants and scale economy of power production, and the waste of resource can also be avoided. At last, case results show that the proposed model is efficient.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.339-344
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• 2001

In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM (Finite Element Method) and BEM (Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta-modeling technique has been developed for solving such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building meta-models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty-six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging meta-model of a train suspension. After each Kriging meta-model is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called SQP (Sequential Quadratic Programming).

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1144_1145
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• 2009

Tidal power station is using the difference of the ebb and flow and the single action tidal power is dependent on tide amplitude and basin volume. Therefore the inflow of basin in rainy season has also effect on the daily power. Also if operating units are changed then starting head too changed. Therefore the number of units are very important for the optimization model. According to our study the primary point when we make a determination of optimization is starting head and governorl control mode. On this study optimization model for tidal power station is considered all of this conditions.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.2
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• pp.33-41
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• 1994

The procedure to design the engine mount is briefly discussed and the optimum shape design process of engine mounting rubber using a parametric approach is suggested. An optimization code is developed to determine the shape to meet the stiffness requirements of engine mounts, coupled with the commercial nonlinear finite element program ABAQUS. A bush type engine mount used in a current passenger car is chosen for an application model. The shape from the result of the parameter optimization is determined as a final model with some modifications. The shape and stiffness of each optimization stage are shown and the stiffness of the optimized model along the principal direction is compared with the design specification of the current model. Finally, an overview of the current status and future works for the engine mount design are discussed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.701-704
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• 2003

Scoliosis is a complex musculoskeletal dieses requiring 3-D treatment with surgical instrumentation. Conventional corrective surgery for scoliosis was done based on empirical knowledge without information of the optimum position and operative procedure. Frequently, post operative change of rib hump increase and shoulder level imbalance caused serious problems in the view of cosmetics. To investigate the effect of correction surgery, a reconstructed 3-D finite element model for King-Moe type V was developed. Vertebrae, clavicle and other bony element were represented using rigid bodies. Kinematic joints and nonlinear bar elements used to represent the intervertebral disc and ligaments according to reported experimental data. With this model, optimization technique was also applied in order to define the optimal magnitudes of correction. The optimization procedure corrected the scoliotic deformities by reducing the objective function by more than 94%. with an associated reduction of the scoliotic descriptors mainly on the frontal thoracic curve.