• 한국연소학회:학술대회논문집
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• 2014.11a
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• pp.19-20
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• 2014

Boiler design should be desinged to maximize thermal efficiency of the system under imposed load requirement and a boiler should be validated for transient operation. If a proper prediction is possible on the transient behavior and transient characteristics of a boiler, one may asses the performance of boiler component, control logics and operation procedures. In this work, dynamic modeling method of boiler is presented and dynamic simulation of load runback scenario was carried out on suprecritical oil-firing boiler.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.146.4-146
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• 2001

Various methods have been proposed for the time series prediction. Most of the conventional methods only optimize parameters of mathematical models, but to construct an appropriate functional form of the model is more difficult in the first place. We employ the Genetic Programming (GP) to construct the functional form of prediction models. Our method is distinguished because the model parameters are optimized by using Back-Propagation (BP)-like method and the prediction model includes discontinuous functions, such as if and max, as node functions for describing complicated phenomena. The above-mentioned functions are non-differentiable, but the BP method requires derivative. To solve this problem, we develop ...

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06b
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• pp.95-100
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• 1996

User's qualities of services (QoS) are the basic requirements involved in distributed multimedia systems. Considering ATM network, ATM adapter cannot control the end-to-end connection satisfying the user's QoS. This paper describes the new concept of a QoS prediction management system in the distributed network and the configuration of it's QoS prediction management architecture and also discusses it's algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.368-368
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• 2000

In this paper, we present forecasting ozone concentration with decision support system. Since the mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, modeling of ozone prediction system has many problems and results of prediction are not good performance so far. Forecasting ozone concentration with decision support system is acquired to information from human knowledge and experiment data. Fuzzy clustering method uses the acquisition and dynamic polynomial neural network gives us a good performance for ozone prediction with ability of superior data approximation and self-organization.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.315-315
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• 2000

In this paper, we perform the time series prediction using the SVM(Support Vector Machine). We make use of two different loss functions and two different kernel functions; i) Quadratic and $\varepsilon$-insensitive loss function are used; ii) GRBF(Gaussian Radial Basis Function) and ERBF(Exponential Radial Basis Function) are used. Mackey-Glass time series are used for prediction. For both cases, we compare the results by the SVM to those by ANN(Artificial Neural Network) and show the better performance by SVM than that by ANN.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.944-952
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• 2001

Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it is desired to combine INS with external aids such as GPS. However GPS informations have a randomly abrupt jump due to a sudden corruption of the received satellite signals and environment, and moreover GPS can\`t provide navigation solutions. In this paper, smoothing and prediction schemes are proposed for GPS`s jump or unavailable GPS. The smoothing algorithm which is designed as a scalar adaptive filter, smooths abrupt jump. The prediction algorithm which is proved by Schuler error model of INS, estimates INS error in appropriate time. The outputs of proposed algorithm apply stable measurements to GPS aided INS Kalman filter. Simulations show that the proposed algorithm can effectively remove measurement jump and predict INS error.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.864-865
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• 2011

Battery Disconnecting System (BDS) is the important equipment in electric vehicle system. Therefore, most of electric vehicle companies, i.e. Hyundai Motors, Renault Motors, General Motors, want to have the reliability of 15 years - 150, 000 miles. Recently, reliability prediction through Siemens Norm SN 29500 is considered without testing. In this paper, we will introduce the standard and various input parameters. Also the case study will be shown for BDS. Prediction model is constructed by listing all the components of BDS. It calculates the $\pi$ factors for each components using the conversion equation in the standard and converts the reference failure rates to the expected operating failure rates. According to the result, the parts which will be improved are EV-Relays.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.2
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• pp.29-35
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• 2020

In this paper, we established a prediction model of fuel consumption at the aircraft's taxi operation. To look for countermeasures to reduce fuel consumption and carbon emissions, Airbus A380's actual ground taxi data was used. As a result, the number of stops or turnings during the taxi operation was not related to fuel consumption. It was confirmed that the amount of fuel consumption in the taxi operation was the taxi time and the thrust change. It can be confirmed that ground control optimization, which is the result of close cooperation between the control organization and the airline, is absolutely necessary to reduce taxi time and minimize the occurrence of thrust change events.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1180-1188
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• 2008

As many systems depend on electronics, concern for fault tolerance is growing rapidly in the safety critical system such as intelligent vehicle. In order to make system fault tolerant, there has been a body of research mainly from aerospace field including predictive hybrid redundancy by Lee. Although the predictive hybrid redundancy has the fault tolerant mechanism to satisfy the fault tolerant requirement of safety crucial system such as x-by-wire system, it suffers form the variability of prediction performance according to the input feature of system. As an alternative to the prediction method of predictive hybrid redundancy for robust fault tolerant, Kalman prediction has attracted some attention because of its well-known and often-used with its structure called Kalman hybrid redundancy. In addition, several numerical simulation results are given where the Kalman hybrid redundancy outperforms with predictive smoothing voter.

• Tribology and Lubricants
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• v.24 no.6
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• pp.291-296
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• 2008

In order to improve the leakage prediction and rotordynamic analysis of an annular seal with a smooth rotor and circumferentially grooved stator, CFD analysis using FLUENT has been performed to determine the groove penetration angle a which is the angle of separation line between control volumes II and III in groove section of Ha and Lee's three-control-volume theory. Validation to the present analysis using new penetration angle determined by the CFD analysis is achieved by comparisons with the results of published Ha and Lee's analysis. For the leakage prediction the present analysis shows slight improvement and CFD results yields the best. Direct damping and cross-coupled stiffness coefficients are predicted better to the experimental ones. However, direct stiffness coefficient is predicted worse.