• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.76.5-76
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• 2001

This paper considers the parameter estimation for the state-space model based time-delay systems in the case that the Lyapunov stability of the system is guaranteed. In order to estimate the parameters, two estimation methods can be proposed which are known as the parallel model and the series parallel model. It is shown that the parameters can be estimated using each method, and also certied that the results are correct by simulations.

• Communications of the Korean Mathematical Society
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• v.28 no.3
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• pp.615-633
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• 2013

We use a power series expansion method to get an analytic approximation value for the quanto option price under the Hull and White stochastic volatility model, which turns out to be accurate enough by comparing with the simulation prices using Monte Carlo method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.69-73
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• 1996

Tool wear monitoring is very important aspect in metal cutting because tool wear effects quarity and precision of workpiece, tool life etc. In this study we detected force signal through tool dynamometer in turning and using it we conducted 6th AR modeling and fractal analysis. Finally the back-propagation model of the neural network is utilized to monitor tool wear and features are extracted through AR model and fractal analysis.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.861-864
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• 1993

This research provides the results of a trial to generate the chaos by using nonlinear function constructed by fuzzy inference rules. The chaos generation function or chaotic behavior can be obtained by using Takagi-Sugeno fuzzy model with some constraint of the relationship of its parameters. Two examples are shown in this research. The first is simple example that construct of logistic image by fuzzy model. The second is more complicated one that provide the chaotic time series by non-linear autoregression based on fuzzy model. Simulated results are shown in these examples.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.491-493
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• 2003

Load foretasting model used generally such as times series and econometric regression model often doesn't reflect the load characteristics of small remote islands. Therefore, in this paper load demand forecast is peformed using EGARCH-M non-linear forecasting model.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.165-174
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• 2018

The model using time series data can be considered as a flood forecasting model of a small river due to its efficiency for model development and the advantage of rapid simulation for securing predicted time when reliable data are obtained. Transfer Function Noise (TFN) model has been applied hourly flood forecast in Italy, and UK since 1970s, while it has mainly been used for long-term simulations in daily or monthly basis in Korea. Recently, accumulating hydrological data with good quality have made it possible to simulate hourly flood prediction. The purpose of this study is to assess the TFN model applicability that can reflect exogenous variables by combining dynamic system and error term to reduce prediction error for tributary rivers. TFN model with hourly data had better results than result from Storage Function Model (SFM), according to the flood events. And it is expected to expand to similar sized streams in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.136-145
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• 2006

SWAT includes a lot of parameters related with geography, hydrological time series, land management and water pollution, etc. So, it needs many spatial, non-spatial and time series data to run SWAT. If SWAT is operated in conjunction with GIS, we can use database which includes model input data and do all the processes which covers data creation, model input and analysis of simulation results in a system. The objective of this study is to develop HyGIS-SWAT which is the interface system to couple the SWAT model and HyGIS. To achieve this object, system operation process based on HyGIS-SWAT data model is evaluated and databases are designed and established. As a result, HyGIS-SWAT prototype system is developed. HyGIS data model and HyGIS-Model operation process can be applied effectively to the development of HyGIS-SWAT. The technologies from this study can be used as base technology to develop another HyGIS application which connect HyGIS with models.

• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.51-59
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• 2000

A dynamic model, which combined time series model with distributed-lag model, is applied to understand the relationship between rainfall and groundwater level. In the model, rainfall with distribution lags and past groundwater level as a dependent variables were used to estimate present groundwater level. The distribution of the lagged rainfall effects for groundwater levels was modeled by Almon polynomials. The model was applied to Banglim and Tanbu groundwater stations in Pyungchang river and Bocheong stream watershed which are representative basins for International Hydrological Program (IHP). The dynamic model represents observed groundwater levels very well and can be used to predict the levels. The model parameters reflect hydraulic characteristics of aquifer. In addition, from the parameters it appears that the increase in groundwater level due to rainfall takes place significantly within first two days of the rainfall event. The rainfall of the order of 18mm/day and 30mm/day at Banglim and Tanbu, respectively, had no significant effect on the groundwater levels.

• Economic and Environmental Geology
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• v.29 no.6
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• pp.713-724
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• 1996

The time-series resident solute concentrations, monitored at two field plots using the automated 144-channel TDR system by Kim (this issue), are used to investigate the dominant transport mechanism at field scale. Two models, based on contradictory assumptions for describing the solute transport in the vadose zone, are fitted to the measured mean breakthrough curves (BTCs): the deterministic one-dimensional convection-dispersion model (CDE) and the stochastic-convective lognormal transfer function model (CLT). In addition, moment analysis has been performed using the probability density functions (pdfs) of the travel time of resident concentration. Results of moment analysis have shown that the first and second time moments of resident pdf are larger than those of flux pdf. Based on the time moments, expressed in function of model parameters, variance and dispersion of resident solute travel times are derived. The relationship between variance or dispersion of solute travel time and depth has been found to be identical for both the time-series flux and resident concentrations. Based on these relationships, the two models have been tested. However, due to the significant variations of transport properties across depth, the test has led to unreliable results. Consequently, the model performance has been evaluated based on predictability of the time-series resident BTCs at other depths after calibration at the first depth. The evaluation of model predictability has resulted in a clear conclusion that for both experimental sites the CLT model gives more accurate prediction than the CDE model. This suggests that solute transport at natural field soils is more likely governed by a stream tube model concept with correlated flow than a complete mixing model. Poor prediction of CDE model is attributed to the underestimation of solute spreading and thus resulting in an overprediction of peak concentration.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.88-99
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• 2007

Soil moisture is one of the essential components in determining surface hydrological processes such as infiltration, surface runoff as well as meteorological, ecological and water quality responses at watershed scale. This paper discusses soil moisture transfer processes measured at hillslope scale in the Gwangneung forest catchment to understand and provide the basis of stochastic structures of soil moisture variation. Measured soil moisture series were modelled based upon the developed univariate model platform. The modeling consists of a series of procedures: pre-treatment of data, model structure investigation, selection of candidate models, parameter estimation and diagnostic checking. The spatial distribution of model is associated with topographic characteristics of the hillslope. The upslope area computed by the multiple flow direction algorithm and the local slope are found to be effective parameters to explain the distribution of the model structure. This study enables us to identify the key factors affecting the soil moisture distribution and to ultimately construct a realistic soil moisture map in a complex landscape such as the Gwangneung Supersite.