• Journal of KIISE:Databases
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• v.33 no.3
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• pp.261-270
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• 2006

Positional data of moving objects can be regularly sampled in order to minimize the cost of data collection in LBS. Since position data which are regularly sampled cannot include the changes of position occurred between sampling periods, sampled position data differ from the data predicted by a time parameterized linear function. Uncertain position data caused by these differences make the accuracy of the range queries for present positions diminish in the TPR tree. In this paper, we propose the uncertainty region to handle the range queries for uncertain position data. The uncertainty region is defined by the position data predicted by the time parameterized linear function and the estimated uncertainty error. We also present the weighted recent uncertainty error policy and the kalman filter policy to estimate the uncertainty error. For performance test, the query processor based by the uncertainty region is implemented in the TPR tree. The experiments show that the Proposed query processing methods are more accurate than the existing method by 15%.

• Journal of the Korean earth science society
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• v.32 no.3
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• pp.249-264
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• 2011

A multi-Gaussian kriging approach extended to space-time domain is presented for uncertainty modeling as well as time-series mapping of environmental variables. Within a multi-Gaussian framework, normal score transformed environmental variables are first decomposed into deterministic trend and stochastic residual components. After local temporal trend models are constructed, the parameters of the models are estimated and interpolated in space. Space-time correlation structures of stationary residual components are quantified using a product-sum space-time variogram model. The ccdf is modeled at all grid locations using this space-time variogram model and space-time kriging. Finally, e-type estimates and conditional variances are computed from the ccdf models for spatial mapping and uncertainty analysis, respectively. The proposed approach is illustrated through a case of time-series Particulate Matter 10 ($PM_{10}$) concentration mapping in Incheon Metropolitan city using monthly $PM_{10}$ concentrations at 13 stations for 3 years. It is shown that the proposed approach would generate reliable time-series $PM_{10}$ concentration maps with less mean bias and better prediction capability, compared to conventional spatial-only ordinary kriging. It is also demonstrated that the conditional variances and the probability exceeding a certain thresholding value would be useful information sources for interpretation.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.144-149
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• 2006

This paper deals with a balanced model reduction for uncertain nonlinear systems via T-S fuzzy approach. We define a generalized controllability/observability gramian and obtain a balanced state space model using generalized gramians which can be obtained from solutions of linear matrix inequalities. We present a balanced model reduction scheme by truncating not only state variables but also uncertain elements. An upper bound of the model reduction error will also be suggested. In order to demonstrate the efficacy of our method, a numerical example will be presented.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.60-60
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• 2020

기후변화 및 지구온난화로 인한 자연재해 규모가 점차 대형화, 다양화되고 있어 이로 인한 피해도 증대되고 있다. 특히, 다양한 시설과 인구밀도가 높은 도심 지역은 집중호우, 태풍, 홍수 등 자연재해에 취약하여 인적·물적 피해 위험성이 매우 높다. 방재 시설확보 및 개선을 통한 더 높은 안정성 및 기상예보를 통한 대응, 대책을 통한 피해 저감이 이루어지고 있다. 그러나 일반적으로 제공되는 단일 수치모형 기반의 결정론적 기상예측정보는 기상 상태, 선행시간, 모형 매개변수 등으로 인한 불확실성이 매우 크며 이에 대한 정보가 제공되지 않다. 이러한 문제점을 보완하기 위해 앙상블 수치모델 정보와 기상레이더 자료 기반의 단기 예측정보가 활용이 가능하다. 그러나, 앙상블 수치모델의 불확실성, 기상레이더 기반 예측정보의 짧은 예측 선행시간으로 인해 수문학적 모형에 입력자료로 활용은 어려운 실점이다. 본 연구에서는 지점 관측자료의 시간적 연속성, 기상레이더 자료의 공간적 연속성, 앙상블 예측정보의 선행시간 정보를 융합하여 기상예측정보에 대한 불확실성 개선 및 선행시간에 따른 정확도를 높일 방법을 제안하였다. 기상청에서 제공하는 앙상블 예측자료인 LENS 자료, 레이더 강수량, ASOS 관측자료 기반으로 분석이 수행되었으며 분석결과는 예측강수량을 활용하는 분야에 긍정적 영향을 미칠 것으로 기대된다.

• Journal of Korea Water Resources Association
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• v.31 no.5
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• pp.553-564
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• 1998

For the proper design and management of underground storage cavern, groundwater flow around cavern should be analyzed. Since this flow is influenced by spatial nonuniformity of hudraulic conductivity, the two-dimensional finite element flow model incorporating stochastic concepts was developed to analyze influences due to this nonuniformity. Monte Carlo technique was applied to obtain an approximate solution for two-dimensional, steady flow in a stochastically defined nonuniform medisu. For this purpose, the values of hydraulic conductivity were generated for each element with known mean and standard deviations. The uncertainty in model prediction depends on both the nonuniformity in hydraulic conductivity and the natures of the flow system such as water curtain and boundary condition. Therefore the uncertainties in predicted hydraulic head and gradient are the greatest where the mean hydraulic gradients are relatively large and far from the boundaries. Especially, we relate these uncertainties with well known gas tightness condition.

• Geophysics and Geophysical Exploration
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• v.13 no.4
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• pp.330-335
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• 2010

In order to estimate the confidence level of the velocity distribution shown in a velocity image reconstructed from a travel-time tomography, the ray coverage and the inversion characteristics of the system matrix were investigated. The targets of the analysis is the first arrival travel-time, the raypath information, and the resulting velocity model. The ray coverage, degree of ray and model coupling, was estimated by the number of rays and total ray length in a velocity grid, and information regarding the resolution and uncertainties involved in the reconstructed velocity model was derived from the results of the SVD analysis of the system matrix that relates the data space (first arrival travel times) to the model space (velocity distribution in tomogram).

• Journal of the Korean Geotechnical Society
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• v.19 no.2
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• pp.123-133
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• 2003

A practical statistical approach that can be used to model various sources of uncertainty systematically is presented in the context of reliability analysis of slope stability. New expressions for probabilistic characterization of soil properties incorporate sampling and measurement errors, as well as spatial variability and its reduced variance due to spatial averaging. The stochastic nature of seismic loading is studied by generating a large series of hazard-compatible artificial motions, and by using them in subsequent response analyses. The analyses indicate that in a seismically less active region such as the Korean Peninsular, a moderate variability in soil properties has an effect as large as the characterization of earthquake hazard on the computed risk of slope failure and excessive slope deformations.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.543-549
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• 2021

In this paper, a robust transfer alignment method is proposed for a strapdown inertial navigation system(SDINS) with norm-bounded parametric uncertainties. The uncertainties are described by the energy bound constraint, i.e., sum quadratic constraint(SQC). It is shown that the SQC can be coverted into an indefinite quadratic cost function in the Krein space. Krein space Kalman filter is designed by modifying the measurement matrix and the variance of measurement noises in the conventional Kalman filter. Since the proposed Krein space Kalman filter has the same recursive structure as a conventional Kalman filter, the proposed filter can easily be designed. The simulation results show that the proposed filter achieves robustness against measurement time delay and high dynamic environment of the vehicle.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6A
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• pp.1001-1011
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• 2006

It is a general agreement that exact statistical solutions can be found by a Monte Carlo technique. Due to difficulties, however, in the numerical generation of random fields, which satisfy not only the probabilistic distribution but the spectral characteristics as well, it is recognized as relatively difficult to find an exact response variability of a structural response. In this study, recognizing that the random field assumes a constant over the domain under consideration when the correlation distance tends to infinity, a semi-theoretical solution of response variability is proposed for general structures. In this procedure, the probability density function is directly used. It is particularly noteworthy that the proposed methodology provides response variability for virtually any type of probability density function, and has capability of considering correlations between multiple random variables.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.30-30
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• 2015

유역에 내린 강우의 총량은 홍수나 갈수 측면에서 매우 중요하다. 점 강우량에 의해 측정된 강우량을 이용하여 유역 총강우량으로 환산하는 과정에 많은 오차가 포함되어 있다. 선행연구에 따르면, 우량계를 통한 강우관측에서 언더캐치(undercatch)에 의한 계통오차는 일반적으로 5~16%, 우연오차는 약 5%가 발생된다고 보고하였으며, 점 우량계 자료를 내삽하여 공간자료로 변환할 경우 0.1km 규모에서 표준오차가 4~14%, 1km 규모에서는 33~45%, 10km 규모에서는 약 65% 정도 발생된다고 한다. 이러한 우량계 관측오차 및 강우자료 처리과정에서 발생되는 오차는 유역의 유출량 계산에 영향을 주어 홍수예보 정확도를 크게 떨어뜨릴 수 있다. 우리나라에서는 지금까지 유역 총강우량 산정 측면에서 지점강우량의 불확실성에 대한 연구가 많이 이루어지지 못하였다. 본 연구에서는 우리나라에서 주로 사용되고 있는 전도형 우량계를 이용하여 소규모 구역에서 관측되는 강우관측의 불확실성을 분석하고자 하였다. 연구에 사용된 우량계는 0.5mm 급 표준 전도형 우량계로 정밀도는 시간당 1~100mm 기준으로 ${\pm}1%$를 기록하여 기상검정규격인 ${\pm}3%$를 만족하고 있다. 이 우량계는 한국건설기술연구원 안동하천실험센터 내에 장애물이 없는 평지에 60m 간격으로 총 6대($2{\times}3$)를 설치하여 2014년 7월 11일부터 9월 2일까지 54일간 관측을 수행하였다. 관측기간 동안 2대의 우량계가 수일동안 강우가 기록되지 않아서 분석에서 제외하였다. 우량계 상호 간의 누적강우량(54일간)을 비교한 결과 2.5~25.5mm의 차이를 나타냈다. 강우강도별 강우량 합계를 비교한 결과 시간당 1mm 이상에서는 약 1%의 차이가 났으며, 시간당 15mm 이상에서는 7.4%의 차이를 나타내어 강도가 큰 강우사상에서 우량계 간의 관측오차가 더 크게 나타났다. 또한 우량계 상호 간의 상관계수를 분석한 결과, 우량계 간의 거리가 가까울수록 그리고 누적시간이 길수록 상관계수는 커지는 것을 확인할 수 있었다. 도출된 결과를 토대로 하면 앞서 언급한 바와 같이 점 우량계 자료를 내삽하거나 유역 또는 계산격자의 대푯값으로 사용하여 1시간 이하 단위로 유출모의를 할 경우 심각한 오차를 발생시킬 수 있음을 시사한다. 보다 신뢰성 있는 홍수예보와 효율적인 유역관리를 위해서는 점 중심의 강우 관측이 아닌 면적 우량에 대한 관측이 이루어져야 하며 이를 위한 기술의 개발이 필요하다.