• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1018-1023
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• 1992

In this paper we proposed the systematic method of reducing the order of controller with robustness. State space formulae for all controllers is found by solving two coupled J-lossless coprime factorizations and model reduction problem. To reduce the order of controller, balanced truncation and Hankel approximation are used.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 1992.08a
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• pp.84-89
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• 1992

파랑변형 예측모델로서는 타원형 편미분 방정식 형태인 완경사 방정식(Berkhoff, 1972)이 있으며 이는 파랑의 굴절, 회절, 반사등의 변형을 재현할 수 있으나 수치해석상 어려운점이 있으며 많은 기억용량과 계산시간이 소요되어 일반적이지 못한 단점이 있다.(중략)

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.731-732
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• 2012

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.11
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• pp.2390-2398
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• 2002

For integrity analysis of nuclear reactor pressure vessel, including the Pressurized thermal shock analysis, the fast and accurate calculation of the stress intensity factor at the crack tip is needed. For this, a simple approximation scheme is developed and the resulting stress intensity factors for axial semi-elliptical cracks in cylindrical vessel under various loading conditions are compared with those of the finite element method and other approximation methods, such as Raju-Newman's equation and ASME Sec. Xl approach. For these, three-dimensional finite-element analyses are performed to obtain the stress intensity factors for various surface cracks with t/R = 0.1. The approximation methods, incorporated in VINTIN (Vessel INTegrity analysis-INner flaws), utilizes the influence coefficients to calculate the stress intensity factor at the crack tip. This method has been compared with other solution methods including 3-D finite clement analysis for internal pressure, cooldown, and pressurized thermal shock loading conditions. The approximation solutions are within $\pm$2.5% of the those of FEA using symmetric model of one-forth of a vessel under pressure loading, and 1-3% higher under pressurized thermal shock condition. The analysis results confirm that the VINTIN method provides sufficiently accurate stress intensity factor values for axial semi-elliptical flaws on the surface of the reactor pressure vessel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.936-941
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• 2003

Density evolution was developed as a method for computing the capacity of low-density parity-check(LDPC) codes under the sum-product algorithm [1]. Based on the assumption that the passed messages on the belief propagation model can be approximated well by Gaussian random variables, a modified and simplified version of density evolution technique was introduced in [2]. Recently, the min-sum algorithm was applied to the density evolution of LDPC codes as an alternative decoding algorithm in [3]. Next question is how the min-sum algorithm is combined with a Gaussian approximation. In this paper, the capacity of various rate LDPC codes is obtained using the min-sum algorithm combined with the Gaussian approximation, which gives a simplest way of LDPC code analysis. Unlike the sum-product algorithm, the symmetry condition [4] is not maintained in the min-sum algorithm. Therefore, the variance as well as the mean of Gaussian distribution are recursively computed in this analysis. It is also shown that the min-sum threshold under a gaussian approximation is well matched to the simulation results.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1175-1182
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• 2011

In this paper, properties of exact confidence interval and some approximate confidence intervals of hyper-geometric parameter, that is the probability of success p in the population is discussed. Usually, binomial distribution is a well known discrete distribution with abundant usage. Hypergeometric distribution frequently replaces a binomial distribution when it is desirable to make allowance for the finiteness of the population size. For example, an application of the hypergeometric distribution arises in describing a probability model for the number of children attacked by an infectious disease, when a fixed number of them are exposed to it. Exact confidence interval estimation of hypergeometric parameter is reviewed. We consider the approximation of hypergeometirc distribution to the binomial and normal distribution respectively. Approximate confidence intervals based on these approximation are also adequately discussed. The performance of exact confidence interval estimates and approximate confidence intervals of hypergeometric parameter is compared in terms of actual coverage probability by small sample Monte Carlo simulation.

• Journal of Environmental Science International
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• v.24 no.8
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• pp.1023-1036
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• 2015

A reliable streamflow forecasting is essential for flood disaster prevention, reservoir operation, water supply and water resources management. This study proposes a hybrid model for river stage forecasting and investigates its accuracy. The proposed model is the wavelet packet-based artificial neural network(WPANN). Wavelet packet transform(WPT) module in WPANN model is employed to decompose an input time series into approximation and detail components. The decomposed time series are then used as inputs of artificial neural network(ANN) module in WPANN model. Based on model performance indexes, WPANN models are found to produce better efficiency than ANN model. WPANN-sym10 model yields the best performance among all other models. It is found that WPT improves the accuracy of ANN model. The results obtained from this study indicate that the conjunction of WPT and ANN can improve the efficiency of ANN model and can be a potential tool for forecasting river stage more accurately.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.03a
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• pp.101-105
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• 1998

A large system predictor, which can perform prediction of sales trend in a huge number of distribution centers, is presented using neural predictive model. There are 20,000 number of distribution centers, and each distribution center need to forecast future demand in order to establish a reasonable inventory policy. Therefore, the number of forecasting models corresponds to the number of distribution centers, which is not possible to estimate that kind of huge number of accurate models in ERP (Enterprise Resource Planning)module. Multilayer neural net as universal approximation is employed for fitting the prediction model. In order to improve prediction accuracy, a sequential simulation procedure is performed to get appropriate network structure and also to improve forecasting accuracy. The proposed simulation procedure includes neural structure identification and virtual predictive model generation. The predictive model generation consists of generating virtual signals and estimating predictive model. The virtual predictive model plays a key role in tuning the real model by absorbing the real model errors. The complement approach, based on real and virtual model, could forecast the future demands of various distribution centers.

• Journal of the Korean Society of Propulsion Engineers
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• v.19 no.6
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• pp.1-9
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• 2015

This paper introduces a zero-dimensional modeling on the plasma generation in electrothermal gun operation. The plasma generator consists of alumina bore and aluminum electrodes which is electrically powered by outer pulse forming network and, traditionally, its numerical simulations have employed time-dependent one-dimensional governing equations. However, by assuming isothermal approximation along the bore and choked bore exit condition, present analysis simplifies the mass and energy equations into zero-dimensional approximation of plasma conditions coupled with mass ablation model and plasma property evaluation. The numerical results show good agreement with the corresponding one-dimensional computations and thus verify the present modeling approach.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.415-418
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• 2003

Fuzzy modelling has the approximation property far the given input-output relationship. Especially, Takagi-Sugeno fuzzy models are widely used because they show very good performance in the nonlinear function approximation problem. But generally there is not the systematic method incorporating the human expert's knowledge or experience in fuzzy rules and it is not easy to End the membership function of fuzzy rule to minimize the output error as well. The ANFIS (Adaptive Network-based Fuzzy Inference Systems) is one of the neural network based fuzzy modelling methods that can be used with various type of fuzzy rules. But in this model, it is the problem to End the optimum number of fuzzy rules in fuzzy model. In this paper, a new fuzzy modelling method based on the ANFIS and pruning techniques with the measure named impact factor is proposed and the performance of proposed method is evaluated with several simulation results.