• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.294-294
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• 2012

홍수위험도 추정에 있어서 불확실성은 수리, 수문, 구조, 환경 및 사회경제적인 불확실성과 관련 있으며, 수리 수문학적 불확실성은 주로 수리 수문학적 현상과 그 과정에 대한 불완전한 지식, 그리고 그 과정에 포함된 매개변수들에 대한 불완전한 지식과 관련이 있다. 이러한 여러 가지 불확실성은 홍수위험도 추정에 있어서의 불확실성에 중요한 요인으로 작용하므로 불확실성을 설명하기 위한 통계적 정보는 신뢰성 있는 홍수위험도 추정에 있어서 선행조건이라 할 수 있다. 이러한 불확실성 요인중 강우의 공간분포에 대한 신뢰성 있는 추정은 수자원 해석 및 설계에 있어서 필수적인 요소이다. 강우장의 공간변동성에 대한 고해상도 추정은 홍수, 특히 돌발홍수의 원인이 되는 국지성 호우의 확인 및 분석에 있어서 중요하다. 또한 강우의 공간 변동성에 대한 고려는 면적평균강우량 추정의 정확도를 향상시키는데 있어서 중요하며, 강우-유출모델의 모의결과에 대한 신뢰도를 향상시키는데 큰 영향을 미친다. 최근 공간자료에 대한 공간분포예측에 있어서 공간상관성을 고려할 수 있는 공간통계학적 기법의 적용이 증가하고 있으며, 이러한 공간통계학적 기법의 적용에 있어서 신뢰성 있는 모델 매개변수의 추정 및 불확실성 평가는 공간분포 예측결과에 대한 신뢰성을 향상시키는데 중요한 역할을 한다. 외국의 경우 공간분포예측 및 모의, 매개변수의 불확실성 평가 등과 관련하여 활발한 연구가 이루어지고 있는 반면 국내 수자원 분야에서는 아직까지 활발한 연구가 이루어지고 있지 않은 실정이다. 국내의 수문설계실무에서와 같이 확률홍수량을 강우빈도분석과 강우-유출모델을 이용하여 추정할 경우 확률홍수량 추정에 있어서 확률강우량 및 공간분포에 대한 불확실성과 강우-유출모델에서의 불확실성이 확률홍수량 추정에서의 불확실성에 영향을 미치며, 이후 연피해기대치 추정과 같은 홍수위험도 추정의 불확실성에도 영향을 미치게 된다. 따라서 본 연구에서는 강우공간분포의 불확실성을 고려한 홍수량 추정을 위하여 공간추계모의 기법인 CEM을 적용하여 강우공간분포의 불확실성을 정량화하고 강우-유출모델의 입력 강우량에 대한 확률분포를 추정하였다. 강우-유출해석의 경우 유효우량 및 홍수수문곡선 산정을 위하여 국내 수자원 실무에서 가장 많이 적용되고 있는 NRCS CN 기법, Clark 및 Muskingum 모델을 적용하였다. 이로부터 강우공간분포의 불확실성 추정, 소유역별 입력 강우량에 대한 확률분포의 추정 및 재현기간별 확률홍수량의 불확실성 정량화 방안을 제시하였다. 이러한 결과들은 풍수해저감대책, 유역종합치수대책 등 각종 수자원 계획 및 설계실무에서 확률홍수량 및 홍수 또는 재해위험도 추정의 신뢰성을 향상시킬 수 있는 방법론적 대안으로 활용될 수 있을 것으로 판단된다.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.965-978
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• 2006

This paper implements an automatic Korean word-spacing system based on word-recognition using morpheme unigrams and the pattern that the categories of those morpheme unigrams share within a candidate word. Although previous work on Korean word-spacing models has produced the advantages of easy construction and time efficiency, there still remain problems, such as data sparseness and critical memory size, which arise from the morpho-typological characteristics of Korean. In order to cope with both problems, our implementation uses the stochastic information of morpheme unigrams, and their category patterns, instead of word unigrams. A word's probability in a sentence is obtained based on morpheme probability and the weight for the morpheme's category within the category pattern of the candidate word. The category weights are trained so as to minimize the error means between the observed probabilities of words and those estimated by words' individual-morphemes' probabilities weighted according to their categories' powers in a given word's category pattern.

• Journal of Soil and Groundwater Environment
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• v.10 no.5
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• pp.52-60
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• 2005

The conceptual model of under-sampled study area will include a great amount of uncertainty. In this study, we investigate the applicability of Markov chain model in a spatial domain as a tool for minimizing the uncertainty arose from the lack of data. A new formulation is developed to generalize the previous two-dimensional coupled Markov chain model, which has more versatility to fit any computational sequence. Furthermore, the computational algorithm is improved to utilize more conditioning information and reduce the artifacts, such as the artificial parcel inclination, caused by sequential computation. A generalized 20 coupled Markov chain (GCMC) is tested through applying a hypothetical soil map to evaluate the appropriateness as a substituting model for conventional geostatistical models. Comparing to sequential indicator model (SIS), the simulation results from GCMC shows lower entropy at the boundaries of indicators which is closer to real soil maps. For under-sampled indicators, however, GCMC under-estimates the presence of the indicators, which is a common aspect of all other geostatistical models. To improve this under-estimation, further study on data fusion (or assimilation) inclusion in the GCMC is required.

• Korea Real Estate Review
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• v.28 no.3
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• pp.21-35
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• 2018

The recent performance of residential mortgages demonstrated how default risk operated separately from prepayment risk. In this study, we investigated the determinants of the borrowers' decisions pertaining to early termination through default from the mortgage performance data released by Freddie Mac, involving securitized mortgage loans from January 2011 to September 2013. We estimated a Cox-type, proportional hazard model with a single risk on fundamental factors associated with default options for individual mortgages. We proposed a mortgage default model that included two specifications of delinquency: one using a delinquency binary variable, while the other using a delinquency probability. We also compared the results obtained from two specifications with respect to goodness-of-fit proposed in the spirit of Vuong (1989) in both overlapping and nested models' cases. We found that a model with our proposed delinquency probability variable showed a statistically significant advantage compared to a benchmark model with delinquency dummy variables. We performed a default prediction power test based on the method proposed in Shumway (2001), and found a much stronger performance from the proposed model.

• Tunnel and Underground Space
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• v.15 no.2 s.55
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• pp.145-156
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• 2005

MODFLOW, 3-D finite difference code, is widely used to model groundwater flow and has been used to assess the effect of excavations on the groundwater system due to construction of subways and mountain tunnels. The results of numerical analysis depend on boundary conditions, initial conditions, conceptual models and hydrogeological properties. Therefore, its accuracy can only be enhanced using more realistic and field oriented input parameters. In this study, SA(simulated annealing) was used to integrate hydraulic conductivities from a few of injection tests with geophysical reference images. The realizations of hydraulic conductivity random field are obtained and then groundwater flows in each geostatistically equivalent media are analyzed with a numerical simulation. This approach can give probabilistic results of groundwater flow modeling considering the uncertainty of hydrogeological medium. In other words, this approach makes it possible to quantify the propagation of uncertainty of hydraulic conductivities into groundwater flow.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.12
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• pp.1351-1358
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• 2011

To approximate the threshold of the fault detection and diagnosis (FDD) system, validation of the measurements is mandatory. Naturally, the system shows uncertainties due to measuring sensors - mostly thermocouples or RTDs - and due to repeatability. The uncertainty of a thermocouple comes from natural variation or a drift of the thermocouple measurement. Considering the natural variation behaves like zero-mean white noise, its natural variation can be characterized closely by the steady-state standard deviation. However, residuals between measurements and no-fault references in FDD systems show a statistical distribution with various uncertainties. In this paper, steady-state variations of measurement residuals were investigated by utilizing built-in temperature sensors in a heat pump for the model development and the final application.

• Journal of the Korean GEO-environmental Society
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• v.13 no.11
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• pp.81-91
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• 2012

This paper mainly deals with the analysis of probabilistic characteristics of the disturbed function proposed to predict dynamic behavior of Geosynthetic-soil interface as the lining and cover systems used in waste landfills. Calibration and statistical property estimation of the parameters in the disturbed function model were first performed using many experimental data obtained from a new multi-purpose interface apparatus (M-PIA). In order to analyze the effect due to changes in chemical degradation and normal loads condition, probabilistic properties such as mean, coefficient of variation and distribution type of the disturbed function were evaluated using both the LHS method known to be a very efficient sampling scheme and the estimated statistical property of A and Z. As a result, variation of the disturbed function is found to range approximately from 10~28% according to the level of ${\xi}_D$ and Weibull appears to be the most adequate distribution type at almost all levels of ${\xi}_D$. It is concluded that a probabilistic safety assessment method for Geosynthetic-soil interface considering uncertainty in shear strength can be developed by utilizing probabilistic properties of the disturbed function obtained in this study.

• The Journal of Engineering Geology
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• v.21 no.1
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• pp.1-13
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• 2011

Joint roughness is one of the most important parameters in analysis of rock slope stability. Especially in probabilistic analysis, the random properties of joint roughness influence the probability of slope failure. Therefore, a large dataset on joint roughness is required for the probabilistic analysis but the traditional direct measurement of roughness in the field has some limitations. Terrestrial LiDAR has advantagess over traditional direct measurement in terms of cost and time. JRC (Joint Roughness Coefficient) was calculated from statistical parameters which are known from quantitative methods of converting the roughness of the material surface into JRC. The mean, standard deviation and distribution function of JRC were obtained, and we found that LiDAR is useful in obtaining large dataset for random variables.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1900-1904
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• 2007

지금까지 수공구조물의 설계와 기존 시설의 안전도를 평가시 수문, 수리 및 경제학적 함수들에서 발생하는 불확실성을 설명하기 위하여 안전율 또는 여유고를 증가시키거나 이들 정보의 양과 질을 증가시켜 데이터베이스를 확장하고 측정오차를 최소화시키며, 전통적인 통계해석을 적용하였다. 공공의 안전을 확보하기 위하여 설계과정에 안전율 또는 여유고가 도입되었으나 이것은 단순히 보다 높은 재현기간의 적용을 의미하며, 수문현상이 가지는 추계학적 특성보다 확정론적인 근거로부터 안전설계 개념이 개발되었다. 수자원 계획시 고려되는 부하와 저항은 확정론적인 고정치가 아니라 시간에 따라 변하고 동적이며, 무작위적이므로 확률 변수로서 고려되어야 한다. 이에 따라 최근 수자원 계획과정에서 불확실성 해석에 의한 위험도 분석 개념이 도입되고 있으며, 특히 이상기후 및 집중호우의 빈발, 급격한 도시화로 인한 유출양상의 변화 등으로 급증하고 있는 훙수피해를 감안할 때 설계빈도의 상향조정과 같은 확정론적인 방법보다는 매개변수 또는 함수의 불확실성을 고려한 위험도 해석의 필요성이 더욱 증대되고 있는 실정이다. 따라서 본 논문에서는 수자원 계획시 입력자료 및 매개변수의 불확실성과 불확실성의 분리를 고려한 홍수량의 산정 및 각 매개변수의 영향을 평가하여 홍수위험도 해석에 있어서 모델 매개변수의 영향 규명과 처리방안을 제시하고자 한다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.6
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• pp.417-423
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• 2019

In this investigation, a set of seismic fragility curves for RC bridges in Korea is derived by considering variations of the representative analytical model. The dimensions and specifications of the model are determined, based on statistical analysis of the inventory of RC bridges in Korea. Variations of important modeling parameters such as material properties, size of structural members, and dimension of the bridge are defined based on statistical studies of the bridges. The OpenSees program is utilized for the analysis to represent the inelastic behavior of RC members. A systematic approach is developed to perform a large volume of inelastic dynamic analysis, in which continuous variation of the modeling parameters are programmed to appropriately represent the characteristics of RC bridges in Korea.