• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.381-381
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• 2020

자료동화(Data Assimilation) 기법은 실시간 수문학적 예측에 있어 정확도 향상을 위해 필수적인 과정이다. 가장 대중적으로 사용되는 기법들 중 하나가 모델 상태변수와 매개변수를 동시에 업데이트할 수 있는 이중 앙상블 칼만 필터(Dual Ensemble Kalman Filter)이다. 이 방법은 정확도 개선 및 적용의 용이성 때문에 많은 연구 분야에서 사용되어져 왔지만, 앙상블을 생성하는 과정에서 상당시간이 소요되는 단점이 존재한다. 본 연구에서는 상태변수와 매개변수를 동시에 업데이트 하면서 홍수 예측의 정확성을 보장할 뿐만 아니라, 앙상블 생성에 있어 계산 효율을 크게 향상시킬 수 있는 기법을 제안한다. Polynomial Chaos Expansion(PCE) 기법을 사용하여 앙상블 칼만 필터를 모방(mimic)할 수 있는 새로운 대체필터(Surrogate Filter)를 개발하는 것을 목표로 한다. 구체적으로 대체필터를 구성하기 위한 다양한 필터를 설계하였다. 첫째 시간에 대해서 PCE가 변화하지 않는 '불변 필터'(즉, 전체 예측기간에 대해 하나의 필터를 사용하여 자료동화할 수 있는 대체필터)와, 매 시간마다 PCE가 변화하는 '시변 필터'(즉, 예측하는 매 시간마다 새로운 필터를 생성해야 하는 대체필터)를 설계하여 적용성, 정확성, 예측성 등을 비교하였다. 또한, PCE의 하이퍼 매개변수를 최적화하기 위한 최적의 프레임 워크가 제안되어, 대체필터를 구축하는 데 효율을 높이고 PCE의 과적합(overfitting) 현상을 피할 수 있도록 하였다. 본 연구에서 제안된 기법은 기존 단일 및 이중 앙상블 칼만 필터(EnKF)의 결과와 비교 검증하였으며, 그 결과는 다음과 같다. (1) 대체필터의 대부분은 원래 EnKF와 비슷한 정도의 불확실성을 설명할 수 있음; (2) 모든 대체 필터는 선행시간이 짧은 경우의 예측에 있어 우수한 결과를 제공하며, 시변 필터가 불변 필터보다 더 정확한 예측 결과를 제공함; (3) 대체필터는 원래 앙상블 칼만필터보다 최대 500배 빠른 속도로 성능을 향상시킬 수 있음. 제안된 대체필터는 자료동화를 수행하는 기존필터와 비슷한 정도의 정확성, 매우 향상된 효율성을 보장함을 확인할 수 있었다.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.3
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• pp.29-43
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• 2024

Legally protected species are one of the crucial considerations in the field of natural ecology when conducting environmental impact assessments (EIAs). The occurrence of legally protected species, especially 'Endangered Wildlife' designated by Ministry of Environment, significantly influences the progression of projects subject to EIA, necessitating clear investigations and presentations of their habitats. In perspective of statistics, a minimum of 30 occurrence coordinates is required for population prediction, but most of endangered wildlife has insufficient coordinates and it posing challenges for distribution prediction through modeling. Consequently, this study aims to propose modeling methodologies applicable when coordinate data are limited, focusing on Rodgersia podophylla, representing characteristics of endangered wildlife and northern plant species. For this methodology, 30 random sampling coordinates were used as input data, assuming little survey data, and modeling was performed using individual models included in BIOMOD2. After that, the modeling results were evaluated by using discrimination capacity and the reality reflection ability. An optimal modeling technique was proposed by ensemble the remaining models except for the MaxEnt model, which was found to be less reliable in the modeling results. Alongside discussions on discrimination capacity metrics(e.g. TSS and AUC) presented in modeling results, this study provides insights and suggestions for improvement, but it has limitations that it is difficult to use universally because it is not a study conducted on various species. By supporting survey site selection in EIA processes, this research is anticipated to contribute to minimizing situations where protected species are overlooked in survey results.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.241-265
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• 2023

A corporate insolvency prediction model serves as a vital tool for objectively monitoring the financial condition of companies. It enables timely warnings, facilitates responsive actions, and supports the formulation of effective management strategies to mitigate bankruptcy risks and enhance performance. Investors and financial institutions utilize default prediction models to minimize financial losses. As the interest in utilizing artificial intelligence (AI) technology for corporate insolvency prediction grows, extensive research has been conducted in this domain. However, there is an increasing demand for explainable AI models in corporate insolvency prediction, emphasizing interpretability and reliability. The SHAP (SHapley Additive exPlanations) technique has gained significant popularity and has demonstrated strong performance in various applications. Nonetheless, it has limitations such as computational cost, processing time, and scalability concerns based on the number of variables. This study introduces a novel approach to variable selection that reduces the number of variables by averaging SHAP values from bootstrapped data subsets instead of using the entire dataset. This technique aims to improve computational efficiency while maintaining excellent predictive performance. To obtain classification results, we aim to train random forest, XGBoost, and C5.0 models using carefully selected variables with high interpretability. The classification accuracy of the ensemble model, generated through soft voting as the goal of high-performance model design, is compared with the individual models. The study leverages data from 1,698 Korean light industrial companies and employs bootstrapping to create distinct data groups. Logistic Regression is employed to calculate SHAP values for each data group, and their averages are computed to derive the final SHAP values. The proposed model enhances interpretability and aims to achieve superior predictive performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.9-17
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• 2017

Characteristics of aerodynamic damping ratios of a helical $180^{\circ}$ model which shows better aerodynamic behavior in both along-wind and across-wind responses on a super tall building was investigated by an aeroelastic model test. The aerodynamic damping ratio was evaluated from the wind-induced responses of the model by using Random Decrement (RD) technique. Further, various triggering levels in evaluation of aerodynamic damping ratios using RD technique were also examined. As a result, it was found that when at least 2000 segments were used for evaluating aerodynamic damping ratio for ensemble averaging, the aerodynamic damping ratio can be obtained more consistently with lower irregular fluctuations. This is good agreement with those of previous studies. Another notable observation was that for square and helical $180^{\circ}$ models, the aerodynamic damping ratios in along-wind direction showed similar linear trends with reduced wind speeds regarding of building shapes. On the other hand, for the helical $180^{\circ}$ model, the aerodynamic damping ratio in across-wind direction showed quite different trends with those of the square model. In addition, the aerodynamic damping ratios of the helical $180^{\circ}$ model showed very similar trends with respect to the change of wind direction, and showed gradually increasing trends having small fluctuations with reduced wind speeds. Another observation was that in definition of triggering levels in RD technique on aerodynamic damping ratios, it may be possible to adopt the triggering levels of "standard deviation" or "${\sqrt{2}}$ times of the standard deviation" of the response time history if RD functions have a large number of triggering points. Further, these triggering levels may result in similar values and distributions with reduced wind speeds and either may be acceptable.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.4
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• pp.206-216
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• 2017

The temporal distribution of the turbulence kinetic energy (TKE) and the vertical component of Reynolds stresses ($-{\bar{u^{\prime}w^{\prime}}}$) was measured during one wave period under high wave energy conditions. The wave data were obtained at Hujeong Beach in the east coast of Korea at January 14~18 of 2017 when an extratropical cyclone was developed in the East Sea. Among the whole thousands of waves measured during the period, hundreds of regular waves that had with similar pattern were selected for the analysis in order to give three representing mean wave patterns using the ensemble average technique. The turbulence properties were then estimated based on the selected wave data. It is interesting to find out that $-{\bar{u^{\prime}w^{\prime}}}$ has one clear peak near the time of flow reversal while TKE has two peaks at the corresponding times of maximum cross-shore velocity magnitudes. The distinguished pattern of Reynolds stress indicates that vertical fluxes of such properties as suspended sediments may be enhanced at the time when the horizontal flow direction is reversed to disturb the flows, supporting the turbulence convection process proposed by Nielsen (1992). The characteristic patterns of turbulence properties are examined using the CADMAS-SURF Reynolds-Averaged Navier-Stokes (RANS) model. Although the model can reasonably simulate the distribution of TKE pattern, it fails to produce the $-{\bar{u^{\prime}w^{\prime}}}$ peak at the time of flow reversal, which indicates that the application of RANS model is limited in the prediction of some turbulence properties such as Reynolds stresses.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.12
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• pp.1-8
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• 2006

An experimental study was carried out in order to investigate the influence of Reynolds number on the near-wake of an oscillating airfoil. An NACA 0012 airfoil was sinusoidally pitched at the quarter chord point, and is oscillated over a range of instantaneous angles of attack of $\pm$6$^{\circ}$. An X-type hot-wire probe was employed to measure the near-wake of an oscillating airfoil, and the smoke-wire visualization technique was used to examine the flow properties of the boundary layer. The free-stream velocities were 1.98, 2.83 and 4.03 m/s and the corresponding chord Reynolds numbers were 2.3${\times}10^4$, 3.3$\times$104 and 4.8${\times}10^4$, respectively. The frequency of airfoil oscillation was adjusted to fix a reduced frequency of K=0.1. The results show that the properties of the boundary layer and the near-wake can dramatically be distinguished in the range of Reynolds numbers between 2.3${\times}10^4$ and 3.3${\times}10^4$, on the other hand, it is similar in the cases of Re=3.3$\times$104 and 4.8$\times$104. This is caused by that the unsteady separation point is dramatically delayed in case of Re= 2.3${\times}10^4$.

• Journal of Korea Water Resources Association
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• v.46 no.1
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• pp.59-71
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• 2013

The lack of sufficient flood data being kept across Korea has made it difficult to assess reliable estimates of the design flood while relatively sufficient rainfall data are available. In this regard, a rainfall simulation based derivation technique of flood frequency curve has been proposed in some of studies. The main issues in deriving the flood frequency curve is to develop the rainfall simulation model that is able to effectively reproduce extreme rainfall. Also the rainfall-runoff modeling that can convey uncertainties associated with model parameters needs to be developed. This study proposes a systematic approach to fully consider rainfallrunoff related uncertainties by coupling a piecewise Kernel-Pareto based multisite daily rainfall generation model and Bayesian HEC-1 model. The proposed model was applied to generate runoff ensemble at Daechung Dam watershed, and the flood frequency curve was successfully derived. It was confirmed that the proposed model is very promising in estimating design floods given a rigorous comparison with existing approaches.

• Journal of Biosystems Engineering
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• v.25 no.2
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• pp.97-106
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• 2000

To develop the grain moisture meter using microwave free space transmission technique, a 10.5GHz microwave signal with the power of 11mW generated by an oscillar with a dielectric resonator is transmitted to an isolator and radiated from a transmitting $2{\times}2$ microstrip patch array antenna into the sample holder filled with the 12 to 26%w.b. of Korean Hwawung paddy rice. the microwave signal, attenuated through the grain with moisture, is collected by a receiving $2{\times}2$ microstrip patch array antenna and detected using a Shottky diode with excellent high frequency characteristic. A pair of light and simple microstrip patch array antenna for measurement of grain moisture content is designed and implemented on atenflon substrate with trleative dielectric constant of 2.6 and thickness of 0.54 by using Ensemble ver. 4.02 software. The aperture of microstrip patch arrays is 41 mm width and 24mm high. The characteristics of microstrip patch antenna such as grain. return loss, and bandwidth are 11.35dBi, -38dB and 0.35GHz($50^{\circ}$ at far-field pattern of E and H plane. The width of the sample holder is large enough to cover the signal between the antennas temperature and bulk density respectively. The calibration model for measurement of grain moisture content is proposed to reduce the effects of fluectuations in bulk density and temperature which give serious errors for the measurements . From the results of regression analysis using the statistically analysis method, the moisture content of grain samples (MC(%)) is expressed in terms of the output voltage(v), temperature (t), and bulk density of samples(${\rho}b$)as follows ;$$MC(%)\;=\;(-3.9838{\times}10^{-8}{\times}v^{3}+8.023{\times}10^{-6}{\times}v^{2}-0.0011{\times}v-0.0004{\times}t+0.1706){\frac{1}{{\rho}b}}{\times}100$ Its determination coefficient, standard error of prediction(SEP) and bias were found to be 0.9855, 0.479%w.b. and -0.0.369 %w.b. respectively between measured and predicted moisture contents of the grain samples.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.74-74
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• 2016

복잡한 지형에서 컴퓨터를 이용한 물리적 기반 수치모의는 합리적인 시간내에 연산을 완료하기 위해 대개 큰 연산장비 들을 요구한다. 더욱이 모의되는 현상이 시간단계마다 갱신되어지는 동역학적 현상에 기반된 비정상상태일 때 연산성능은 고려되어지는 가장 중요한 주제가 될 수 있다. 연산 시간을 줄이기 위한 가장 널리 이용되는 전략중의 하나는 적절한 수의 프로세서를 이용하는 병렬 기법이다. 최근 들어 연산속도를 가속화하기 위해 다수의 코어를 이용한 OpenMP 와 MPI 기법들이 병렬해석기법으로 대두되었고 그래픽 연산장치를 이용한 병렬처리 해석기법도 소개되고 있다. 본 연구에서는 중앙연산장치를 이용한 병렬 해석기법을 이용하여 제내지 침수해석의 적용성을 검토하고 그 결과을 비교하였다. 본 연구를 위해 OpenMP 병렬기법을 이용하여 확산파 침수해석 프로그램의 원시코드를 재작성하여 가상 및 실제 유역에 적용하였다. 해석결과는 분산메모리 병렬해석 기법인 MPI를 도입한 모형의 결과와 비교되었다. OpenMP를 도입한 모형과 MPI를 도입한 경우 유량 및 수심의 경우 오차 허용 한계내에 수렴되어 만족되었으나 그러나 연산 속도의 경우 두 기법간의 자료의 저장 방법 차이로 인해 차이를 나타내었다. 가상 유역에 적용된 결과로 검토된 각 기법의 증속(speedup) 효과는 MPI의 경우 4 코어를 이용하였을 때 최고 2.62 배 정도에 도달하는 것으로 나타났다. OpenMP 를 적용한 경우 2.87 배 정도로 나타나 OpenMP 를 이용하였을 때 증속효과가 조금 더 뛰어났다. 이는 두 기법의 메모리 저장방식의 차이로 인해 자료의 전송량과 전송 시간이 적은 OpenMP 를 도입한 모형에서 MPI 모형 보다 상대적으로 뛰어난 결과를 나타내었다. 실제 유역의 적용을 위해 상대적으로 우수한 증속결과를 나타낸 OpenMP를 도입한 모형을 Malpasset 댐 붕괴 유역에 적용하였다. 적용된 요소의 수는 각각 45254, 11352 개로 비교적 많은 요소를 가진 하류지역에 적용하여 병렬효과를 극대화하고자 하였다. 적용결과 두 경우 모두 병렬 해석 기법을 도입한 모형에서 유속과 침수심 등은 순차적 모형과 동일한 값을 나타내었으나 증속효과로 인한 연산시간은 순차적 모형에서 8.57 배로 나타나 병렬 모형의 상대적으로 빠른 연산속도를 판단할 있었다. 위의 적용결과를 통해 계산 요소들이 많은 2 차원 해석의 경우 기존의 단일 코어를 이용한 순차적 해석은 장시간에 걸치 연산시간으로 인해 작업효율이 낮아지는 결과를 발생시킬 수 있으며 병렬 해석을 도입할 경우 주어진 컴퓨터 자원를 효율적으로 이용가능하여 합리적인 연산시간으로 연산결과를 얻는 것이 가능하여 반복적 통계 기법/Ensemble 해석 등을 이용한 종합적 해석이 좀 더 실용적으로 이루어 질 수 있을 것이라고 판단되었다.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.944-958
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• 2011

Soil hydraulic properties such as hydraulic conductivity or water retention which are costly to measure can be indirectly generated by soil pedotransfer function (PTF) using easily obtainable soil data. The field soil structure description which is routinely recorded could also be used in PTF as an input to reduce the uncertainty. The purposes of this study were to use qualitative morphological soil structure descriptions and soil structural index into PTF and to evaluate their contribution in the prediction of soil hydraulic properties. We transformed categorical morphological descriptions of soil structure into quantitative values using categorical principal component analysis (CATPCA). This approach was tested with a large data set from the US National Pedon Characterization database with the aid of a categorical regression tree analysis. Six different PTFs were used to predict the saturated hydraulic conductivity and those results were averaged to quantify the uncertainty. Quantified morphological description was successively used in multiple linear regression approach to predict the averaged ensemble saturated conductivity. The selected stepwise regression model with only the transformed morphological variables and structural index as predictors predicted the $K_{sat}$ with $r^2$ = 0.48 (p = 0.018), indicating the feasibility of CATPCA approach. In a regression tree analysis, soil structure index and soil texture turned out to be important factors in the prediction of the hydraulic properties. Among structural descriptions size class turned out to be an important grouping parameter in the regression tree. Bulk density, clay content, W33 and structural index explained clusters selected by a two step clustering technique, implying the morphologically described soil structural features are closely related to soil physical as well as hydraulic properties. Although this study provided relatively new method which related soil structure description to soil structure index, the same approach should be tested using a datasets containing the actual measurement of hydraulic properties. More insight on the predictive power of soil structure index to estimate hydraulic properties would be achieved by considering measured the saturated hydraulic conductivity and the soil water retention.