• Journal of Korea Water Resources Association
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• v.39 no.12 s.173
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• pp.997-1012
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• 2006

We have presented a nonparametric stochastic approach for the SOI(Southern Oscillation Index) series that used nonlinear methodology called Nonlinear AutoRegressive(NAR) based on conditional kernel density function and CAFPE(Corrected Asymptotic Final Prediction Error) lag selection. The fitted linear AR model represents heteroscedasticity, and besides, a BDS(Brock - Dechert - Sheinkman) statistics is rejected. Hence, we applied NAR model to the SOI series. We can identify the lags 1, 2 and 4 are appropriate one, and estimated conditional mean function. There is no autocorrelation of residuals in the Portmanteau Test. However, the null hypothesis of normality and no heteroscedasticity is rejected in the Jarque-Bera Test and ARCH-LM Test, respectively. Moreover, the lag selection for conditional standard deviation function with CAFPE provides lags 3, 8 and 9. As the results of conditional standard deviation analysis, all I.I.D assumptions of the residuals are accepted. Particularly, the BDS statistics is accepted at the 95% and 99% significance level. Finally, we split the SOI set into a sample for estimating themodel and a sample for out-of-sample prediction, that is, we conduct the one-step ahead forecasts for the last 97 values (15%). The NAR model shows a MSEP of 0.5464 that is 7% lower than those of the linear model. Hence, the relevance of the NAR model may be proved in these results, and the nonparametric NAR model is encouraging rather than a linear one to reflect the nonlinearity of SOI series.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.65-73
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• 2017

This study analyzed the peak drought severity and drought duration of the Cheongmicheon watershed from 1985 to 2015 to assess the lag time of peak drought severity between several drought indices. Standardized Precipitation Index (SPI) based on precipitation and Standardized Precipitation Evapotranspiration Index (SPEI) based on precipitation and evapotranspiration were applied as meteorological drought indices. Streamflow Drought Index (SDI) based on runoff data was applied as hydrological drought index. In case of SDI, we used Soil and Water Assessment Tool (SWAT) model for simulation of daily runoff data. As a result, the time of peak drought severity of SDI occurred after the occurrence of SPI and SPEI. The lag time for the peak drought severity, on average, between SDI and SPI was 0.59 months while SDI and SPEI was 0.79 months. As compared with SDI, the maximum delay was 2 months for both SPI and SPEI. This study results also shows that even though the rainfall events were able to cope with meteorological droughts, they were not always available to solve the hydrological droughts in the same time.

• Journal of the Korean Vacuum Society
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• v.5 no.4
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• pp.284-291
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• 1996

We have implemented a fast pressure control system for the transport chamber of a high vacuum cluster tool for advance semiconductor fabrication and evaluated its performance. To overcome the typically slow response of mass flow controllers, the modified experimental method is used very effectively to optimize the pressure control procedure. We successfully obtained quite fast pressure control by adjusting the starting time and eht tuning constants by the Ziegler-Nichols method. In the transport pressure $10\times 10^{-5}$ torr, actual pressure control starts from 4 sec after an initial gas load of 2.1 sccm. As a result, optimum conditions for the tuning constants are the rise rate of 0.02 torr/sec, the lag time of 0.15 sec, and the sampling period of 0.5 sec. Then the settling time is about 9 sec within about $\pm$0.5% for the referenced value. This settling time is enhanced above 75 percents in comparison with conventional experimental method. To account for the experimental effects observed, a theoretical model was developed. This experimental result has a tendency to fit with the theoretical result of $\omega$=-1.0.

• Asia-Pacific Journal of Business
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• v.7 no.1
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• pp.1-10
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• 2016

This study attempts to investigate the effects of different types of debts on economic growth in Bangladesh using time series data spanning from 2000 to 2015. In this study, the RDL model has been applied to determine the long run relationship among the selected variables. The result of the ARDL model shows that there exists a long term relationship between economic growth and the debt variables. It was evident from the findings that there exists bidirectional causality between public sector external debt and economic growth. Causality between private external debt and economic growth has been found to be insignificant. However, causality between domestic debt and economic growth showed a unidirectional causality from domestic debt to economic growth and not vice versa. Causality tests suggest that impact of domestic debt on economic growth is more effective compared to external debts.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.1 no.3
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• pp.228-234
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• 1989

This paper describes the experimental thermal performance results of four experimental model buildings insulated differently. For the purpose of examining the thermal characteristics of external walls and indoor thermal conditions, four experimental model buildings are constructed as externally insulated, internally insulated, non-insulated &light-weight curtain wall types with different K-values and heat capacities, respectively.
Through the measurements of temperatures at various points and solar insolation, the effects of insulation and heat capacities are evaluated, and the evaluated effects of each experimental model buildings are compared. Hence, the characteristics of temperature profiles, time-lag effects and decrement factors are discovered.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.57-72
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• 2020

The price of iron ore has continued to fluctuate with high demand and supply from many countries and companies. In this business environment, forecasting the price of iron ore has become important. This study developed the machine learning model forecasting the price of iron ore a one month after the trading events. The forecasting model used distributed lag model and deep learning models such as MLP (Multi-layer perceptron), RNN (Recurrent neural network) and LSTM (Long short-term memory). According to the results of comparing individual models through metrics, LSTM showed the lowest predictive error. Also, as a result of comparing the models using the ensemble technique, the distributed lag and LSTM ensemble model showed the lowest prediction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.155-163
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• 2019

The knowledge about drought propagation is very important in accurate estimation of hydrological drought characteristics and efficient development of early warning system. This study investigated a probabilistic relationship of drought propagation based on Bayesian network model for historic period and for future projection under climate change scenario RCP 8.5 over the Han River basin. The results revealed that the propagation rate and lag time have increasing and decreasing trends from the historic period of 1967-2013 to the future periods of 2014-2053 and 2054-2100 under climate change, respectively. The probabilistic results of Bayesian model revealed that the probability of occurrence of lag time varied spatially and decreased when the intensity of meteorological drought changed from moderate to severe and extreme condition during 1967-2013. The values of probability increased in the first future period of 2014-2053 in several sub-basins and slight decreased in the second period of 2054-2100. The proposed probabilistic results will be useful for the decision makers to develop related policies with an appropriate insight toward the future drought status.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.629-641
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• 2021

In this study, a two-dimensional numerical model (Nays2DH) was applied to analyze the process of morphological changes in the river channel bed depending on the changes in the amount of flooding after fully opening the Sejong weir, which was constructed upstream of the Geum River. For this, numerical simulations were performed by assuming the flow conditions, such as a non-uniform flow (NF), unsteady flows (single flood event, SF), and a continuous flood event (CF). Here, in the cases of the SF and CF, the normalized hydrograph was calculated from real flood events, and then the hydrograph was reconfigured by the peak flow discharge according to the scenario, and then it was employed as the flow discharge at the upstream boundary condition. In this study, to quantitatively evaluate the morphological changes, we analyzed the time changes in the bed deformation the bed relief index (BRI), and we compared the aerial photographs of the study area and the numerical simulation results. As simulation results of the NF, when the steady flow discharge increases, the ratio of lower width to depth decreases and the speed of bar migration increases. The BRI initially increases, but the amount of change decreased with time. In addition, when the steady flow discharge increases, the BRI increased. In the case of SF, the speed of bar migration decreased with the change of the flow discharge. In terms of the morphological response to the peak flood discharge, the time lag also indicated. In other words, in the SF, the change of channel bed indicates a phase lag with respect to the hydraulic condition. In the result of numerical simulation of CF, the speed of bar migration depending on the peak flood discharges decreased exponentially despite the repeated flood occurrences. In addition, as in the result of SF, the phase lag indicated, and the speed of bar migration decreased exponentially. The BRI increased with time changes, but the rate of increase in the BRI was modest despite the continuous peak flooding. Through this study, the morphological changes based on the hydrological characteristics of the river were analyzed numerically, and the methodology suggested that a quantitative prediction for the river bed change according to the flow characteristic can be applied to the field.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1840-1841
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• 2006

Plants with long time-delays can not be often controlled effectively using a simple PID controller. The main reason for this is that the additional phase lag contributed by the time-delay tends to destabilize the closed-loop system. The stability problem can be solved by smith predictor. However, in this case responses are very sensitive to the estimated model errors. To reduce sensitive problem, this paper is presented based on virtual reference feedback tuning of the time delay plant using the closed-loop test to find parameters for a PID controller using the closed-loop test data.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.1025-1030
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• 2009

It is known that the classical tuning formula for typical PID controllers in general provides unsatisfactory results for industrial plants where the time delay exceeds the dominant lag time. For this reason, alternative strategies have been studied in order to cope with this problem and the most popular scheme is the Smith Predictor(SP). In this paper, the dynamic model of a unit apartment in the district heating system, which is the control process effected by the dead-time, is developed, and the on/off room temperature control method with the SP simulate using Matlab-Simulink. The simulation results show that the SP works effectively in outdoor temperature variation.