• 전기학회논문지
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• 제61권3호
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• pp.394-400
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• 2012

In this paper, charging modes of series resonant converter for a high voltage energy storage capacitor are compared in terms of charging time, peak resonant current, normalized peak resonant current and voltage in each operation mode. Operating principles of the full bridge series resonant converter with capacitor load are explained and analyzed in discontinuous and continuous operation mode. Based on the analysis and simulation result, $0.6{\omega}_r$ < ${\omega}_s$ < $0.75{\omega}_r$ and $1.3{\omega}_r$ < ${\omega}_s$ < $1.4{\omega}_r$ are evaluated to the best range of switching frequency for charging of an high voltage energy storage capacitor. 1.8 kJ/s SRC prototype is assembled with TI 28335 DSP controller and 40 kJ, 7 kV energy storage capacitor. Design rules based on the comparative analysis are verified by experiment.

• Journal of Information Display
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• 제10권4호
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• pp.188-194
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• 2009

Conventional stereoscopic (3D) displays using binocular parallax generate unnatural conflicts between convergence and accommodation. These conflicts can affect the observer's ability to fuse binocular images and may cause visual fatigue. In this study, time series changes in visual fatigue and depth sensation when viewing stereoscopic images with changing parallax were examined. In particular, the physiological changes, including the subjective symptoms of visual fatigue, when viewing five parallax conditions, were examined. Then a comparative analysis of the 2D and 3D conditions was performed based on the visual function. To obtain data regarding the visual function, the time series changes in the spontaneous-blinking rate before and during the viewing of 3D images were measured. The time series change results suggest that 2D and 3D images cause significantly different types of visual fatigue over the range of binocular disparity.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제11권4호
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• pp.275-285
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• 2004

In this paper, the time series models for the number of reported death claims of compulsory automobile liability insurance in Korea are studied. We found that IMA${(0, 1, 1)}\;{\times}\;{(0, 1, 1)}_{12}$ would the most appropriate model for the number of reported claims by the Box-Jenkins method.

• 무역학회지
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• 제45권5호
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• pp.75-89
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• 2020

The purpose of this paper was to analyze the trend of container volume using the Seasonal Autoregressive Intergrated Moving Average (SARIMA) model. To this end, this paper used monthly time-series data of the East Sea Rim from 2001 to 2019. As a result, the SARIMA(2,1,1)12 model was identified as the most suitable model, and the superiority of the SARIMA model was demonstrated by comparative analysis with the ARIMA model. In addition, to confirmed forecasting accuracy of SARIMA model, this paper compares the volume of predict container to the actual volume. According to the forecast for 24 months from 2020 to 2021, the volume of containaer increased from 60,100,000Ton in 2020 to 64,900,000Ton in 2021

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.1-6
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• 2011

As large-scale building projects have recently increased for the residential, commercial and office facilities, construction costs for these projects have become a matter of great concern, due to their significant construction cost implications, as well as unpredictable market conditions and fluctuations in the rate of inflation during the projects' long-term construction periods. In particular, recent volatile fluctuations of construction material prices fueled such problems as cost forecasting. This research develops a time series model using the Box-Jenkins approach and material price time series data in Korea in order to forecast trends in the unit prices of required materials. Building information modeling (BIM) approaches are also used to analyze injection times of construction resources and to conduct quantity take-off so that total material prices can be forecast. To determine an optimal time series model for forecasting price trends, comparative analysis of predictability of tentative autoregressive integrated moving average (ARIMA) models is conducted. The proposed BIM-based time series forecasting model can help to deal with sudden changes in economic conditions by estimating material prices that correspond to resource injection times.

• 유통과학연구
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• 제12권3호
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• pp.25-32
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• 2014

Purpose - This study reviews changes in the steel export-import structure between Korea and Japan using a trade related index; it focuses on analyzing comparative advantage based on time-series analysis statistics data using the trade intensity index (TII), revealed comparative advantage index (RCA), and trade specialization index (TSI). Research design, data, and methodology - In terms of their economic phase, Korea and Japan have a mutually complementary character. Therefore, this study aims to understand each country's trade structure to strengthen Korea-Japan economic cooperation, examine trade drawbacks, analyze factors that affect trade, and identify ways to improve and expand trade. Results - The results indicate immense potential for mutual cooperation and complementariness, which will yield guaranteed adequate profits comparable to those of any regional economic integrated community. Conclusion - From our viewpoint, Northeast economic cooperation can facilitate industry technological cooperation with Japanese partners in the prevailing environment that is characterized by increasing competition among industries and the need to secure stable resource supplies as well as the expansion of the export market and diversification, which can have significant positive implications.

• Journal of information and communication convergence engineering
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• 제20권2호
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• pp.125-130
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• 2022

In modern society, as many data are used for research or commercial purposes, the value of data is gradually increasing. In related fields, research is being actively conducted to collect valuable data, but it is difficult to collect proper data because the value of collection is determined according to the performance of existing sensors. To solve this problem, a method to effectively reduce noise has been proposed, but there is a point in which performance is degraded due to damage caused by noise. In this paper, a device capable of collecting time series data was designed to correct such data noise, and a correction technique was performed by giving an error value based on the representatively collected ultrafine dust data, and then comparing before and after Compare performance. For the correction method, Kalman, LPF, Savitzky-Golay, and Moving Average filter were used. Savitzky-Golay filter and Moving Average Filter showed excellent correction rate as an experiment. Through this, the performance of the sensor can be supplemented and it is expected that data can be effectively collected.

• 한국통신학회논문지
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• 제25권6B호
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• pp.1120-1126
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• 2000

Recently, in order to analyze the time series problems that occur in the nature word, and analyzing method using a neural electric network is being studied more than a typical statistical analysis method. A neural electric network has a generalization performance that is possible to estimate and analyze about non-learning data through the learning of a population. In this paper, after collecting weather datum that was collected from 1987 to 1996 and learning a population established, it suggests the weather forecasting system for an estimation and analysis the future weather. The suggested weather forecasting system uses 28*30*1 neural network structure, raises the total learning numbers and accuracy letting the selecting concentration learning about the pattern, that is not collected, using the descending epsilon learning method. Also, the weather forecasting system, that is suggested through a comparative experiment of the typical time series analysis method shows more superior than the existing statistical analysis method in the part of future estimation capacity.

• 한국컴퓨터정보학회논문지
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• 제29권10호
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• pp.1-9
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• 2024

본 연구는 화성 기상 데이터를 대상으로 활성화 함수와 어텐션 메커니즘이 시계열 모델의 성능에 미치는 영향을 평가하기 위해 비교 및 분석한다. 화성의 기상 데이터는 대기 밀도가 낮고, 급격한 온도 변동 및 복잡한 지형 등으로 인해 비선형적이고 불규칙적이다. 본 연구에서는 LSTM, BiLSTM, GRU, BiGRU 아키텍처를 사용하여 다양한 활성화 함수와 어텐션 메커니즘의 효과를 평가한다. 실험에 사용된 활성화 함수는 ReLU, Leaky ReLU, ELU, GELU, Swish, SELU이며, 모델 성능은 MAE와 RMSE 지표로 측정된다. 실험 결과, 어텐션 메커니즘을 통합함으로써 MAE와 RMSE가 모두 향상되었으며, Swish와 ReLU는 최저 온도 예측에서 가장 우수한 성능을 보였다. 반면, GELU와 ELU는 기압 예측에서 성능이 저하되었다. 이러한 결과는 복잡한 시계열 예측의 모델 정확도를 향상하기 위해 적절한 활성 함수와 어텐션 메커니즘을 선택하는 것이 중요함을 보여준다.

• 산업경영시스템학회지
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• 제20권44호
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• pp.243-255
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• 1997

Forecasting the future values of an observed time series is an important problem in many areas, including economics, traffic engineering, production planning, sales forecasting, and stock control. The purpose of this paper is aimed to discover the more efficient forecasting model through the parameter estimation and residual analysis among the quantitative method such as Winters' exponential smoothing model, Box-Jenkins' model, and Kalman filtering model. The mean of the time series is assumed to be a linear combination of known functions. For a parameter estimation and residual analysis, Winters', Box-Jenkins' model use Statgrap and Timeslab software, and Kalman filtering utilizes Fortran language. Therefore, this paper can be used in real fields to obtain the most effective forecasting model.