• Journal of Korea Water Resources Association
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• v.53 no.7
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• pp.557-567
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• 2020

The six current models for estimating pan coefficient were applied to test the applicability of models in Seoul, South Korea. The models are Cuenca's model, Snyder's model, Pereira et al.'s model, Allen et al.'s model, Orang's model, and Raghuwanshi and Wallender's model. The estimated pan coefficients were compared with measured one. The measured pan coefficient was obtained by using measured pan evaporation and FAO Penman-Monteith reference evapotranspiration. Estimated evaporation by using estimated pan coefficients was compared with measured one. Furthermore, model for estimating pan coefficient in Seoul was developed. When applying 6 current models for 10 m, 15 m and 20 m fetch distances, pan coefficient estimates from Snyder's model were most similar to measured pan coefficients for all fetch distances. On the other hand, pan coefficient estimates from Pereira et al.'s model were most different from measured one. Therefore, model for estimating pan coefficient in Seoul was developed by modifying Snyder's model. When applying developed model, estimated monthly average evaporation was 92.1 mm for 10 m, 15 m and 20 m fetch distances and measured one was 91.9 mm, indicating that evaporation estimate from developed model is closest to measured one, compared with those of current models.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.133-144
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• 2016

This paper proposes a parsimonious periodic autoregressive (PAR) model. The proposed model performance is evaluated through an analysis of Korean unemployment rate series that is compared with existing models. We exploit some common features among each seasonality and confirm it by LR test for the parsimonious PAR model in order to impose a parsimonious structure on the PAR model. We observe that the PAR model tends to be superior to existing seasonal time series models in mid- and long-term forecasts. The proposed parsimonious model significantly improves forecasting performance.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.307-307
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• 2021

개념적 강우-유출모형에서 토양수분과 관련된 물리적 거동은 간략화 된 형태로 강우 및 온도자료를 활용하여 중간변량(state variable)으로 간접적으로 고려되고 있다. 특히 강우-유출모형에 초기함수 조건은 선행함수조건을 고려하여 수문지질학적 평가를 통하여 결정되어야 하나, 일반적으로 가정되거나 모형에서 간략화 된 분석과정을 통해 추정되고 있다. 본 연구에서는 토양의 Water Balance 모형 기반의 개념적 토양수분 추정모형을 활용하였다. 토양수분의 시간적 변동성을 평가하는데 있어서 연속적으로 측정된 In-situ 토양수분 자료를 이용하여 모형의 적합성을 평가하였다. Green-Ampt 방법과 중력식 침투방법과 온도를 활용한 증발산 추정기법을 연계한 토양함수 평가 모형을 개발하였다. In-situ 토양수분 자료와 유역의 강수량 및 온도자료를 이용한 관련 매개변수를 Bayesian 기법을 통해 추정하였으며 매개변수의 민감도를 평가하여 제시하였다. 최종적으로 제안된 모형의 활용측면에서 강우-유출모형의 초기함수 조건으로써의 역할을 평가하였다. 구체적으로 첨두유량 및 유출고와 초기함수조건과의 관계를 제시하고 강우-유출모형에서 활용방안을 제시하고자 한다.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.779-793
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• 1998

In this study, for the purpose of water supply planning, we propose a sophisticated multi-period mixed integer programming model that can coordinate the behavior of multi-reservoir operation, minimizing unnecessary spill. It can simulate the system with operating rules which are self- generated by the optimization engine in the algorithm. It is an optimization model in structure, but it indeed simulates the coordinating behavior of multi-reservoir operation. It minimizes the water shortfalls in demand requirements, maintaining flood reserve volume, minimizing unnecessary spill, maximizing hydropower generation release, keeping water storage levels high for efficient hydroelectric turbine operation. This optimization model is a large scale mixed integer programming problem that consists of 3.920 integer variables and 68.658 by 132.384 node-arc incidence matrix for 28 years of data. In order to handle the enormous amount of data generated by a big mathematical model, the utilization of DBMS (data base management system)seems to be inevitable. It has been tested with the Han River multi-reservoir system in Korea, which consists of 2 large multipurpose dams and 3 hydroelectric dams. We demonstrated successfully that there is a good chance of saving substantial amount of water should it be put to use in real time with a good inflow forecasting system.

• Journal of Science Education
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• v.35 no.1
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• pp.48-58
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• 2011

This study was performed to develop a model for mentorship education in the science education institute for the gifted. Existing mentorship education models were focused on R&E, which involved science high school students as research participants. For this purpose, a new model was proposed with comparatively definite stages and terms, and based on the theoretical background concerning science inquiry abilities and scientific creativities or the mentorship education in the science education institute for the gifted. Existing mentorship models for science-gifted students were analyzed and compared with the scientific inquiry process and science paper form. A science paper form consisting of four stages was selected. A new model was constructed consisting of six stages, and this model was modified to be made fit for application to students in the physics mentorship course at the science education institute for the gifted in K National University. Good points and improvable points of the model through the application were identified, and the model was modified accordingly. In conclusion, a new model was proposed as a mentorship model for science-gifted students. This model was constructed using the PREPARATION-INTRODUCTION-METHOD-RESULT-CONCLUSION-FINISH format.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.66-77
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• 2014

UTIS(Urban Traffic Information System) directly collects link travel time in urban area by using probe vehicles. Therefore it can estimate more accurate link travel speed compared to other traffic detection systems. However, UTIS includes some missing data caused by the lack of probe vehicles and RSEs on road network, system failures, and other factors. In this study, we suggest a new model, based on k-NN algorithm, for imputing missing data to provide more accurate travel time information. New imputation model is an adaptive k-NN which can flexibly adjust the number of nearest neighbors(NN) depending on the distribution of candidate objects. The evaluation result indicates that the new model successfully imputed missing speed data and significantly reduced the imputation error as compared with other models(ARIMA and etc). We have a plan to use the new imputation model improving traffic information service by applying UTIS Central Traffic Information Center.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.831-839
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• 2010

Least squares support vector machine (LS-SVM) is a kernel trick gaining a lot of popularities in the regression and classification problems. We use LS-SVM to propose a iterative algorithm for a nonlinear generalized autoregressive conditional heteroscedasticity model in the mean (GARCH-M) model to estimate the mean and the conditional volatility of stock market returns. The proposed method combines a weighted LS-SVM for the mean and unweighted LS-SVM for the conditional volatility. In this paper, we show that nonlinear GARCH-M models have a higher performance than the linear GARCH model and the linear GARCH-M model via real data estimations.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.60-65
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• 2009

In this paper, we propose a new exponential pulse shaping function based on Chebychev identity equation and Bessel coefficients. The proposed pulse shaping function can produce various pulses with the different characteristics in the time and frequency domain by changing its two parameters. By differentiating the exponential pulse shaping function, we obtain new different pulse functions, in which the even order derivatives of the exponential pulse shaping function are orthogonal to its odd order derivatives. To find the efficiency of the proposed exponential pulse shaping function we analyze its essential characteristics and compare them with those of the conventional Gaussian pulses. We can choose the most suitable exponential pulse waveform according to the design criteria of communication systems.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.367-376
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• 2010

Recently various methods were suggested and reviewed for estimating diffusion processes. Out of suggested estimation method, we mainly concerns on the estimation method using saddlepoint approximation method, and we suggest a term saddlepoint approximation(ASP) method which is the simplest saddlepoint approximation method. We will show that ASP method provides fast estimator as much as Euler approximation method(EAM) in computing, and the estimator also has good statistical properties comparable to the maximum likelihood estimator(MLE). By simulation study we compare the properties of ASP estimator with MLE and EAM, for Ornstein-Uhlenbeck diffusion processes.

• Journal of the Korean Society for information Management
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• v.30 no.3
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• pp.183-205
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• 2013

A number of studies and models have focused on collaborative information behavior (CIB) in various contexts as the importance of research on CIB is recognized in information behavior research. This study compared and analyzed the models of CIB developed by Prekop (2002), Reddy and Jansen (2008), Shah (2008), Karunakaran, Spence and Reddy (2010), and Yue and He (2010), and discussed the direction of future studies of CIB. The future research strategies for overcoming the limitation of previous studies and models on CIB are to extend research object and context, to do holistic research approach tracing complexity of CIB, and to debate and verify the models of CIB. In particular, it needs to modify and improve the models based on the empirical research for domestic context.