• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.523-533
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• 2018

The objective of this study is to analyze uncertainties of ensemble-based streamflow prediction method for model parameters and input data. ESP (Ensemble Streamflow Prediction) and BAYES-ESP (Bayesian-ESP) based on ABCD rainfall-runoff model were selected as streamflow prediction method. GLUE (Generalized Likelihood Uncertainty Estimation) was applied for the analysis of parameter uncertainty. The analysis of input uncertainty was performed according to the duration of meteorological scenarios for ESP. The result showed that parameter uncertainty was much more significant than input uncertainty for the ensemble-based streamflow prediction. It also indicated that the duration of observed meteorological data was appropriate to using more than 20 years. And the BAYES-ESP was effective to reduce uncertainty of ESP method. It is concluded that this analysis is meaningful for elaborating characteristics of ESP method and error factors of ensemble-based streamflow prediction method.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.04a
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• pp.21-27
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• 2000

For earthquake hazard estimation the data containing large historical events and recent complete observations with various uncertainty should be used together. The traditional maximum likelihood method is not adequate for this kind work. The maximum probable earthquakes in the Korean Peninsula are estimated by the method of an extended maximum likelihood estimation. The method can handle data with various uncertainty. The maximum probable earthquake in the Korean Peninsula is appeared to be 7.14$\pm$0.34 in magnitude.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.15-18
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• 2003

This paper presents an adaptive control scheme for parking or regulating a nonholonomic mobile robot of an unicycle type with parameter uncertainty. The kinematics can be described with Brockett's nonholonomic integrator. The control law is designed in cylindrical coordinates together with the estimation law for the uncertain parameters such that the controlled signals converge to zero while guaranteeing the boundedness of the estimation errors. The effectiveness of the proposed scheme is demonstrated using simulations.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.543-550
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• 2002

This work is concerned with the estimation of output derivatives and their use for the design of robust controller for linear systems with systems uncertainties due to modeling errors and disturbance. It is assumed that a nominal transfer function model and Quantitative bounds for system uncertainties are known. The developed control schemes are shown to achieve regulation of the system output and ensures boundedness of the system states without imposing any structural conditions on system uncertainties and disturbances. Output derivative estimation is first conducted trough restructuring of the plant in a specific parameterization. They are utilized for constructing robust nonlinear high-gain feedback controller of a SMC(Sliding Mode Controller) Type. The performances of the developed controller are evaluated and shown to be effective and useful through simulation study.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.225-228
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• 2007

This paper presents a geostatistical methodology to model local uncertainty in spatial estimation of sediment grain size with high-resolution remote sensing imagery. Within a multi-Gaussian framework, the IKONOS imagery is used as local means both to estimate the grain size values and to model local uncertainty at unsample locations. A conditional cumulative distribution function (ccdf) at any locations is defined by mean and variance values which can be estimated by multi-Gaussian kriging with local means. Two ccdf statistics including condition variance and interquartile range are used here as measures of local uncertainty and are compared through a cross validation analysis. In addition to local uncertainty measures, the probabilities of not exceeding or exceeding any grain size value at any locations are retrieved and mapped from the local ccdf models. A case study of Baramarae beach, Korea is carried out to illustrate the potential of geostatistical uncertainty modeling.

• Tunnel and Underground Space
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• v.16 no.2 s.61
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• pp.135-145
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• 2006

In this study, conditional simulation was conducted to estimate rock mass rating(RMR) in unsurveyed regions. Sequential Gaussian simulation(SGS) and sequential indicator simulation(SIS) were applied for estimating RMR from the bore hole logging data. The uncertainty of SGS and SIS was verified by sample cross validation. A subset composed of 5 bore hole logging data among the original 30 bore hole logging data was set aside as test data. The remainder was training data. The quality of SGS and SIS estimation on the testing data reflects how well it would perform in an unsupervised setting. SGS and SIS were useful stochastic methods to estimate the spatial distribution of rock mass classes correctly and assess the uncertainty of estimation quantitatively. The result of conditional simulation can offer useful information of rock mass classes such as RMR in unsurveyed regions.

• Journal of Wetlands Research
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• v.12 no.3
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• pp.155-163
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• 2010

The flash flood is characterized as flood leading to damage by heavy rainfall occurred in steep slope and impervious area with short duration. Flash flood occurs when rainfall exceeds Flash Flood Guidance(FFG). So, the accurate estimation of FFG will be helpful in flash flood forecasting and warning system. Say, if we can reduce the uncertainty of rainfall-runoff relationship, FFG can be estimated more accurately. However, since the rainfall-runoff models have their own parameter characteristics, the uncertainty of FFG will depend upon the selection of rainfall-runoff model. This study used four rainfall-runoff models of HEC-HMS model, Storage Function model, SSARR model and TANK model for the estimation of models' uncertainties by using Monte Carlo simulation. Then, we derived the confidence limits of rainfall-runoff relationship by four models on 95%-confidence level.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.509-520
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• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.348-350
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• 2002

In the high-power tests to be performed on electrical apparatus as switchgears, transformers, insulators, cable and so on the results of tests on these apparatus are extremely important to evaluate the performance of test object. The reliability of the results depends on the reliability of measuring systems used in the laboratories where tests are performed. This paper introduces factors of uncertainty and describes estimation of uncertainty in high-voltage measuring system used in high-power testing LAB. 1 in KERI.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.540-542
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• 2003

In the high-power tests to be performed on electrical apparatus as circuit-breaker, load switch, fuse, transformers, insulators, cable and so on, the results of tests on these apparatus are extremely important to evaluate the performance of test object. The reliability of the results depends on the reliability of measuring systems used in the laboratories where tests are performed. This paper deals with factors of uncertainty and describes estimation of uncertainty in new measuring system used in high-power testing LAB. 1 in KERI.