• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.694-698
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• 2008

In hydrology, it is a difficult task to deal with multivariate time series such as modeling streamflows of an entire complex river system. Normal distribution based model such as MARMA (Multivariate Autorgressive Moving average) has been a major approach for modeling the multivariate time series. There are some limitations for the normal based models. One of them might be the unfavorable data-transformation forcing that the data follow the normal distribution. Furthermore, the high dimension multivariate model requires the very large parameter matrix. As an alternative, one might be decomposing the multivariate data into independent components and modeling it individually. In 1985, Lins used Principal Component Analysis (PCA). The five scores, the decomposed data from the original data, were taken and were formulated individually. The one of the five scores were modeled with AR-2 while the others are modeled with AR-1 model. From the time series analysis using the scores of the five components, he noted "principal component time series might provide a relatively simple and meaningful alternative to conventional large MARMA models". This study is inspired from the researcher's quote to develop a multivariate simulation model. The multivariate simulation model is suggested here using Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Three modeling step is applied for simulation. (1) PCA is used to decompose the correlated multivariate data into the uncorrelated data while ICA decomposes the data into independent components. Here, the autocorrelation structure of the decomposed data is still dominant, which is inherited from the data of the original domain. (2) Each component is resampled by block bootstrapping or K-nearest neighbor. (3) The resampled components bring back to original domain. From using the suggested approach one might expect that a) the simulated data are different with the historical data, b) no data transformation is required (in case of ICA), c) a complex system can be decomposed into independent component and modeled individually. The model with PCA and ICA are compared with the various statistics such as the basic statistics (mean, standard deviation, skewness, autocorrelation), and reservoir-related statistics, kernel density estimate.

• 제어로봇시스템학회논문지
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• 제11권1호
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• pp.1-8
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• 2005

A new discretization algorithm for nonlinear systems with delayed input is proposed. The algorithm is represented by Taylor series expansion and ZOH assumption. This method is applied to the sampled-data representation of a nonlinear system with the time-delay input. Additionally, the delay in input is time varying and its amplitude is bounded. The maximum time-delay in input is assumed to be two sampling periods. The mathematical expressions of the discretization method are presented and the ability of the algorithm is tested for some of the examples. The computer simulation proves the proposed algorithm discretizes the nonlinear system with the variable time-delay input accurately.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2562-2567
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• 2005

This paper suggests a new method discretization of nonlinear system using Taylor series expansion and zero-order hold assumption. This method is applied into the sampled-data representation of a nonlinear system with input time delay. Additionally, the delayed input is time varying and its amplitude is bounded. The maximum time-delayed input is assumed to be two sampling periods. Them mathematical expressions of the discretization method are presented and the ability of the algorithm is tested for some of the examples. And 'hybrid' discretization scheme that result from a combination of the ‘scaling and squaring' technique with the Taylor method are also proposed, especially under condition of very low sampling rates. The computer simulation proves the proposed algorithm discretized the nonlinear system with the variable time-delayed input accurately.

• 대한전기학회논문지
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• 제41권3호
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• pp.237-243
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• 1992

The large value of the snubber capacitor is needed to protect the devices in high voltage converters using series connected power semiconductors. But that results in more losses and longer commutation time. So, new technique of series connection is required, which can minimize the value of snubber capacitor and also promote the reliability of high voltage converters. We study on the switching characteristics of series connected power semiconductors and then propose a novel switching algorithm for series-connection which is able to implement not only the dynamic voltage balancing in spite of the differerce of switching characteristics, but the minimization of the value of snubber capacitor, through the change of the value of snubber capacitor by Miller effect. Finally, we illustrate the validity of this synchronization by computer simulation and experimental results.

• 대한전기학회논문지:전력기술부문A
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• 제48권11호
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• pp.1441-1447
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• 1999

A discrete time domain modeling is presented for the pulse-width modulated series resonant converter (PWM-SRC) with a discontinuous current mode. This nonlinear system is linearized about its equilibrium state to obtain a linear discrete time model for the investigation of small signal performances such as the stability and transient response. The usefulness of this small signal model is verified through the dynamic simulation.

• Journal of Electrical Engineering and Technology
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• 제11권6호
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• pp.1548-1555
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• 2016

This paper presents an application of time series analysis in hourly wind speed simulation and forecast in Jeju Island, Korea. Autoregressive - moving average (ARMA) model, which is well in description of random data characteristics, is used to analyze historical wind speed data (from year of 2010 to 2012). The ARMA model requires stationary variables of data is satisfied by power law transformation and standardization. In this study, the autocorrelation analysis, Bayesian information criterion and general least squares algorithm is implemented to identify and estimate parameters of wind speed model. The ARMA (2,1) models, fitted to the wind speed data, simulate reference year and forecast hourly wind speed in Jeju Island.

• Nuclear Engineering and Technology
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• 제52권2호
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• pp.271-278
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• 2020

The investigation into a full-scale 27 m high, by 6 m wide, thermosyphon loop. The simulation model is based on a one-dimensional axially-symmetrical control volume approach, where the loop is divided into a series of discreet control volumes. The three conservation equations, namely, mass, momentum and energy, were applied to these control volumes and solved with an explicit numerical method. The flow is assumed to be quasi-static, implying that the mass-flow rate changes over time. However, at any instant in time the mass-flow rate is constant around the loop. The boussinesq approximation was invoked, and a reasonable correlation between the experimental and theoretical results was obtained. Experimental results are presented and the flow regimes of the working fluid inside the loop identified. The results indicate that a series of such thermosyphon loops can be used as a cavity cooling system and that the one-dimensional theoretical model can predict the internal temperature and mass-flow rate of the thermosyphon loop.

• 한국빅데이터학회지
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• 제7권2호
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• pp.217-224
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• 2022

온라인 쇼핑의 대중화로 인해 많은 의류 상품이 온라인 쇼핑을 통해 소비된다. 의류 상품은 다른 상품과 달리 판매량이 일정하지 않고 날씨의 변화에 따라 판매량이 변화하는 특징이 있다. 따라서 의류 상품의 머신 러닝을 적용한 효율적인 재고 관리 시스템에 대한 연구는 매우 중요하다. 본 논문에서는 의류 업체 'A'로부터 실제 의류 상품 판매량 데이터를 수집하고 판매량 데이터와 같은 시계열 데이터의 예측에 많이 활용되는 LSTM(Long Short-Term Memory)과 Bidirectional-LSTM(Bi-LSTM)의 학습에 사용하여 LSTM과 Bi-LSTM의 판매량 예측 효율을 비교 분석하였다. 시뮬레이션 결과를 통해 LSTM 기술 대비 Bi-LSTM은 시뮬레이션 시간은 더 많이 소요되지만 의류 상품 판매량 데이터와 같은 비주기성 시계열 데이터의 예측 정확도가 동일하다는 것을 확인하였다.

• 한국측량학회지
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• 제38권2호
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• pp.97-107
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• 2020

To analyze temporal and spatial changes in vegetation, it is necessary to determine the associated continuous distribution and conduct growth observations using time series data. For this purpose, the normalized difference vegetation index, which is calculated from optical images, is employed. However, acquiring images under cloud cover and rainfall conditions is challenging; therefore, time series data may often be unavailable. To address this issue, La et al. (2015) developed a multilinear simulation method to generate missing images on the target date using the obtained images. This method was applied to a small simulation area, and it employed a simple analysis of variables with lower constraints on the simulation conditions (where the environmental characteristics at the moment of image capture are considered as the variables). In contrast, the present study employs variables that reflect the growth characteristics of vegetation in a greater simulation area, and the results are compared with those of the existing simulation method. By applying the accumulated temperature, the average coefficient of determination (R²) and RMSE (Root Mean-Squared Error) increased and decreased by 0.0850 and 0.0249, respectively. Moreover, when data were unavailable for the same season, R² and RMSE increased and decreased by 0.2421 and 0.1289, respectively.

• 대한조선학회논문집
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• 제28권2호
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• pp.77-94
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• 1991

일정속도로 항주하는 배에 치하여 생성되는 파를 유한차분법을 이용하여 수치적으로 시뮬레이션 하였다. 지배방정식으로는 3차원 운동량방정식(Euler Eq.)과 연속방정식을 사용하였으며, 직교 좌표 계상에서의 수치계산은 FTCS(forward time/central space)로 차분화하고 시간전진 방법(time marching scheme)으로 수행하였다. 좌표계로 staggered variable mesh system을 채용하여 기존의 계산조직을 개선하므로써, 유체 유동의 변화가 심한 선체주위에 계산 정도를 높이기 위하여 cell을 집중시켰다. 개선된 전산프로그램을 이용하여 Wigley, Series 60($C_{b}$=0.6), 그리고 MS416B 산적화물선 선형등을 대상으로 수치계산을 수행하였으며, 그 결과들을 실험값과 비교하였다.