• Journal of the Korean Geotechnical Society
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• v.20 no.6
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• pp.85-94
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• 2004

In the companion paper, a constitutive model was proposed in order to represent brittleness and dilatancy for cohesionless soils. An optimized design methodology was proposed on the basis of real-coded genetic algorithm in order to determine parameters fir the proposed model systematically. The material parameters were then determined by that algorithm. In order to verify the proposed model, triaxial tests were peformed under $K_0$ conditions for weathered soils. In addition, the results of istropic compressed triaxial tests for granular materials verified the proposed model. For those results the brittle stress-strain relationship and the dilatancy could be modeled reasonably by the proposed model. As a result it was found that the proposed model can appropriately represent the behavior on weathered soil and granular soil.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.3
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• pp.62-68
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• 2002

To satisfy the requirement of the one axis linear positioning system, which is following control of the desired trajectory without following error and is the high positioning accuracy, feed-forward loop having cogging force model is proposed. In the one axis linear positioning system with linear PM motor, cogging force acting as disturbance is modeled analytically. Analytic model of cogging force is verified by result measured from positioning system constructed with linear PM motor. Measured result is very similar with proposed analytic model. Cogging force model is used as feet forward loop in control scheme of linear positioning system. Cogging force feed-forward'loop is obtained from analytic model of cogging farce. Trajectory following error is reduced from 300nm to 100nm by applying the proposed cogging farce feed-forward loop. By using analytic model of cogging force, the control scheme is simplified. Also this analytic model is applicable to calculation of characteristic value of positioning system in design process.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.11
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• pp.619-625
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• 2003

We proposed an optimum PID controller design method of the Smith Predictor It can be applied to various processes. The real process is approximated via the second order plus time delay model (SOPTD) whose parameters are specified through a model reduction algorithm. We already proposed a new model reduction method that considered four point in the Nyquist curve to reduced the steady state error between the real process model and the reduced model using the gradient decent method and the genetic algorithms. In addition, the Smith predictor is used to compensate time delay of the real process model. In this paper, the new optimum parameter tuning algorithm for PID controller of the Smith Predictor is proposed through ITAE as performance index. The Simulation results show the validity and improvement of performance for various processes.

• ETRI Journal
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• v.46 no.3
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• pp.461-472
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• 2024

We propose a network traffic prediction model based on linear and nonlinear model combination. Network traffic is modeled by an autoregressive moving average model, and the error between the measured and predicted network traffic values is obtained. Then, an echo state network is used to fit the prediction error with nonlinear components. In addition, an improved slime mold algorithm is proposed for reservoir parameter optimization of the echo state network, further improving the regression performance. The predictions of the linear (autoregressive moving average) and nonlinear (echo state network) models are added to obtain the final prediction. Compared with other prediction models, test results on two network traffic datasets from mobile and fixed networks show that the proposed prediction model has a smaller error and difference measures. In addition, the coefficient of determination and index of agreement is close to 1, indicating a better data fitting performance. Although the proposed prediction model has a slight increase in time complexity for training and prediction compared with some models, it shows practical applicability.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.49-58
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• 2004

In this talk we proposed an asymptotic test for dimensionality in the latent variable model for probabilistic principal component analysis with missing values at random. Proposed algorithm is a sequential likelihood ratio test for an appropriate Normal latent variable model for the principal component analysis. Modified EM-algorithm is used to find MLE for the model parameters. Results from simulations and real data sets give us promising evidences that the proposed method is useful in finding necessary number of components in the principal component analysis with missing values at random.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.7
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• pp.48-55
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• 1998

We propose a new static current source model and parameter extraction method for AlGaAs/GaAs HBT. The proposed model has 9 parameters describing internal currents and are experessed with the physically meaningful parameters.The proposed parameter extraction method uses the measured dC IV curves and does not need the gummel plt data and any optimization process. the constructed model based on the proposed method predicts the measured data well.

• Communications for Statistical Applications and Methods
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• v.13 no.1
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• pp.125-134
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• 2006

This study confirms that the regression model of endpoint of interval outputs is not identical with that of the other endpoint of interval outputs in interval regression models proposed by Tanaka et al. (1987) and constructs interval regression models using the best regression model given by variable selection. Also, this paper suggests a method to minimize the sum of lengths of a symmetric difference among observed and predicted interval outputs in order to estimate interval regression coefficients in the proposed model. Some examples show that the interval regression model proposed in this study is more accuracy than that introduced by Inuiguchi et al. (2001).

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1250-1260
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• 2020

This study proposes a novel deep neural network model that can accurately detect objects and their relationships in an image and represent them as a scene graph. The proposed model utilizes several multimodal features, including linguistic features and visual context features, to accurately detect objects and relationships. In addition, in the proposed model, context features are embedded using graph neural networks to depict the dependencies between two related objects in the context feature vector. This study demonstrates the effectiveness of the proposed model through comparative experiments using the Visual Genome benchmark dataset.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.19-33
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• 2018

This study proposed a rainfall-runoff model for the purpose of real-time flood warning in urban basins. The proposed model was based on the shot noise process, which is expressed as a sum of shot noises determined independently with the peak value, decay parameter and time delay of each sub-basin. The proposed model was different from other rainfall-runoff models from the point that the runoff from each sub-basin reaches the basin outlet independently. The model parameters can be easily determined by the empirical formulas for the concentration time and storage coefficient of a basin and those of the pipe flow. The proposed model was applied to the total of three rainfall events observed at the Jungdong, Guro 1 and Daerim 2 pumping stations to evaluate its applicability. Summarizing the results is as follows. (1) The unit response function of the proposed model, different from other rainfall-runoff models, has the same shape regardless of the rainfall duration. (2) The proposed model shows a convergent shape as the calculation time interval becomes smaller. As the proposed model was proposed to be applied to urban basins, one-minute of calculation time interval would be most appropriate. (3) Application of the one-minute unit response function to the observed rainfall events showed that the simulated runoff hydrographs were very similar to those observed. This result indicates that the proposed model has a good application potential for the rainfall-runoff analysis in urban basins.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1487-1493
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• 2013

A new simple control method for active power filter, which can realize the complete compensation of harmonics is proposed. In the proposed scheme, a model-based digital current control strategy is presented. The proposed control system is designed and implemented in a form referred to as internal model control structure. This method provides a convenient way for parameterizing the controller in term of the nominal system model, including time-delays. As a result, the resulting controller parameters are directly set based on the power circuit parameters, which make tuning of the controllers straightforward task. In the proposed control algorithm, overshoots and oscillations due to the computation time delay is prevented by explicit incorporating of the delay in the controller transfer function. In addition, a new compensating current reference generator employing resonance model implemented by a DSP(Digital Signal Processor) is introduced. Resonance model has an infinite gain at resonant frequency, and it exhibits a band-pass filter. Consequently, the difference between the instantaneous load current and the output of this model is the current reference signal for the harmonic compensation.