• 한국환경농학회지
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• 제30권3호
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• pp.268-274
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• 2011

본 연구에서는 유량 및 유사량 자료가 부족한 미계측 유역에 대해 Tank모형을 확장하여 궁극적으로 유사량을 평가하는 방법을 제시하였다. 적용 유역은 동해안 타 유역에 비해 유량자료가 확보되어 있는 오십천을 대상으로 집중호우기의 토사유출 특징과 하천의 토사유달률을 구하였다. 본 연구의 주요 결과는 다음과 같다. 1) 실측에 의한 유사량의 산정에 있어서는 먼저 유사량 관계식(sediment rating curve)의 개발이 선행되어야 한다. 본 연구에서는 유량 산정지점에 대해 유량과 병행하여 유사량 관계식을 다음과 같이 구하였다. 오십천 유량-유사량 관계식 : $Q_s=6.017Q^{1.374}$ 2) Tank모형을 적용하여 2006년 강우유출량을 산정한 결과 관측값과 유사한 값($RMSE=1.26m^3/day$)을 얻을 수 있었다. 3) 대상지역의 2006년과 2009년의 연평균 토사전달율 을 비교한 결과 태풍에 따른 집중강우가 있었던 2006년의 토사전달율이 평년의 2009년에 비해 현저하게 높았는데 이는 급격한 강우유출량의 증가에 따른 것이라 보인다. 4) 개량된 Tank모형에 의한 유량 및 토사유출량은 기존의 SRC방법과 비교했을 경우 유사한 경향을 보였으며 이는 향후 유량과 유사량 자료가 부족한 유역에 대해 효과적으로 적용할 수 있을 것으로 본다.

• 한국구조물진단유지관리공학회 논문집
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• 제28권2호
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• pp.69-76
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• 2024

굳지 않은 콘크리트의 유변특성은 콘크리트의 제조 및 성능에 중요한 영향을 미치지만, 새롭게 개발되는 배합과 제조 공법의 다양화로 인하여 기존의 경험적 방법으로는 유변특성의 정확한 예측에 어려움이 있다. 본 연구에서는 시멘트 입자와 같은 나노 수준에서의 입자간 상호작용부터 잔골재와 같은 마이크로 수준에서의 유변학적 성질을 정량적으로 예측하기 위하여 멀티스케일 기법을 적용한 유변특성 예측 모델을 제안하였으며, 시멘트 페이스트의 항복응력, 모르타르의 항복응력 및 소성점도를 예측하기 위하여 YODEL(Yield stress mODEL), Chateau-Ovarlez-Trung 방정식 및 Krieger-Dougherty 방정식을 적용하였다. 일차적으로 시멘트 페이스트의 물-시멘트비(W/C)를 기준으로 하여 페이스트 스케일의 유변특성을 예측하였으며, 예측 결과를 토대로 동일한 W/C에 시멘트-잔골재 부피비(C/S)를 추가한 모르타르 스케일의 유변특성의 예측을 진행하였다. 시멘트 모르타르에 대한 유변특성 실험을 통하여 예측 결과와 실험 결과의 비교를 진행함으로써 예측 모델의 적용 가능성을 평가하였다.

• Genomics & Informatics
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• 제14권4호
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• pp.138-148
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• 2016

The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the "large p and small n" problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN). We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC) for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes.

• Computers and Concrete
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• 제3권6호
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• pp.439-454
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• 2006

This paper develops an artificial neural network (ANN) model for uniformly loaded restrained reinforced concrete (RC) slabs incorporating membrane action. The development of membrane action in RC slabs restrained against lateral displacements at the edges in buildings and bridge structures significantly increases their load carrying capacity. The benefits of compressive membrane action are usually not taken into account in currently available design methods based on yield-line theory. By extending the existing knowledge of compressive membrane action, it is possible to design slabs in building and bridge decks economically with less than normal reinforcement. The processes involved in the development of ANN model such as the creation of a database of test results from previous research studies, the selection of architecture of the network from extensive trial and error procedure, and the training and performance validation of the model are presented. The ANN model was found to predict accurately the ultimate strength of fully restrained RC slabs. The model also was able to incorporate strength enhancement of RC slabs due to membrane action as confirmed from a comparative study of experimental and yield line-based predictions. Practical applications of the developed ANN model in the design process of RC slabs are also highlighted.

• 한국산림과학회지
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• 제79권3호
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• pp.260-268
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• 1990

수확(收穫) 예측(豫測) model이 multicollinearity 문제점(問題點) 가질때 보다 정확한 추정식(推定式)을 얻기 위하여 두 종류의 ridge estimator와 최소(最小) 자승법(自乘法)(OLS)의 추정치를 비교(比較)하였다. 본 연구(硏究)에서 사용(使用)된 ridge estmator는 Mallows's (1973)Cp-like statistic과 Allens's (1974) PRESS-like statistic 이었다. 위의 세가지 estimator 예측(豫測) 능력(能力) 평가(評賣)는 Matney 등(等)(1988)에 의하여 개발(開發)된 수확(收穫) model을 이용(利用)하여 비교(比較)하였다. 사용되어진 자료(資料)는 미국(美國) 남부(南部) 테에다 소나무 시험림(試驗林)의 총(總)522개(個) plot을 이용(利用)하였다. 두 개(個)의 ridge estimator가 최소(最小) 자승법(自乘法)에 의한 추정치 보다 수확(收穫) 예측(豫測) 능력(能力)이 우수(優秀)하였으며, 특히 Mallows's statistic에 의한 ridge estimator가 가장 우수(優秀)하였다. 따라서 ridge estimator는 수확(收穫) 예측(豫測) model의 독립(獨立) 변수(變數) 간(間)에 multicollinearity 문제점(問題點)이 있을 때 최소(最小) 자승법(自乘法)에 의 한 추정치를 대치(代置)할 수 있는 estimator로서 추천(推薦)할 수 있었다.

• 한국유기농업학회지
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• 제29권3호
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• pp.317-332
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• 2021

This study estimated the predictive onion yield through Stepwise regression of big data and weather variables by onion growing season. The economic feasibility of onion observations using big data was analyzed using estimated predictive data. The social welfare effect was estimated through the model of Harberger's triangle using onion yield prediction with big data and it without big data. Predicted yield using big data showed a deviation of -9.0% to 4.2%. As a result of estimating the social welfare effect, the average annual value was 23.3 billion won. The average annual value of social welfare effects if big data was not used was measured at 22.4 billion won. Therefore, it was estimated that the difference between the social welfare effect when the prediction using big data was used and when it was not was about 950 million won. When these results are applied to items other than onion items, the effect will be greater. It is judged that it can be used as basic data to prove the justification of the agricultural observation project. However, since the simple Harberger's triangle theory has the limitation of oversimplifying reality, it is necessary to evaluate the economic value through various methods such as measuring the effect of agricultural observation under a more realistic rational expectation hypothesis in future studies.

• Asian-Australasian Journal of Animal Sciences
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• 제15권3호
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• pp.315-320
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• 2002

Test-day records (n=13677) sampled from 896 ewes in 5-9 (${\mu}$=7.5) monthly test-days were used to estimate genetic and phenotypic parameters of test-day yields, lactation milk yield (TMY), length of the milking period (DAYS) and three measures of persistency of milk yield in Boutsico dairy sheep. Τhe measures of persistency were the slope of the regression line (${\beta}$), the coefficient of variation (CV) of the test-day milk yields and the maximum to average daily milk yield ratio (MA). The estimates of variance components were obtained under a linear mixed model by restricted maximum likelihood. The heritability of test-day yields ranged from 0.15 to 0.24. DAYS were found to be heritable ($h^2$=0.11). Heritability estimates of ${\beta}$, CV and MA were 0.15, 0.13, 0.10, respectively. Selection for maximum lactation yields is expected to result in prolonged milking periods, high rates of decline of yields after peak production, variable test-day yields and higher litter sizes. Selection for flatter lactation curves would reduce lactation yields, increase slightly the length of the milking period and decrease yield variation as well as litter size. The most accurate prediction of TMY was obtained with a linear regression model with the first five test-day records.

• 한국농공학회지
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• 제22권4호
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• pp.108-114
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• 1980

A deterministic conceptual erosion model which simulates detachment, entrainment, transport and deposition of eroded soil particles by rainfall impact and flowing water is presented. Both upland and channel phases of sediment yield are incorporated into the erosion model. The algorithms for the soil erosion and sedimentation processes including land and crop management effects are taken from the literature and then solved using a digital computer. The erosion model is used in conjunction with the modified Kentucky Watershed Model which simulates the hydrologic characteristics from watershed data. The two models are linked together by using the appropriate computer code. Calibrations for both the watershed and erosion model parameters are made by comparing the simulated results with actual field measurements in the Four Mile Creek watershed near Traer, Iowa using 1976 and 1977 water year data. Two water years, 1970 and 1978 are used as test years for model verification. There is good agreement between the mean daily simulated and recorded streamflow and between the simulated and recorded suspended sediment load except few partial differences. The following conclusions were drawn from the results after testing the watershed and erosion model. 1. The watershed and erosion model is a deterministic lumped parameter model, and is capable of simulating the daily mean streamflow and suspended sediment load within a 20 percent error, when the correct watershed and erosion parameters are supplied. 2. It is found that soil erosion is sensitive to errors in simulation of occurrence and intensity of precipitation and of overland flow. Therefore, representative precipitation data and a watershed model which provides an accurate simulation of soil moisture and resulting overland flow are essential for the accurate simulation of soil erosion and subsequent sediment transport prediction. 3. Erroneous prediction of snowmelt in terms of time and magnitute in conjunction with The frozen ground could be the reason for the poor simulation of streamflow as well as sediment yield in the snowmelt period. More elaborate and accurate snowmelt submodels will greatly improve accuracy. 4. Poor simulation results can be attributed to deficiencies in erosion model and to errors in the observed data such as the recorded daily streamflow and the sediment concentration. 5. Crop management and tillage operations are two major factors that have a great effect on soil erosion simulation. The erosion model attempts to evaluate the impact of crop management and tillage effects on sediment production. These effects on sediment yield appear to be somewhat equivalent to the effect of overland flow. 6. Application and testing of the watershed and erosion model on watersheds in a variety of regions with different soils and meteorological characteristics may be recommended to verify its general applicability and to detact the deficiencies of the model. Futhermore, by further modification and expansion with additional data, the watershed and erosion model developed through this study can be used as a planning tool for watershed management and for solving agricultural non-point pollution problems.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• 제2권1호
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• pp.29-36
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• 1998

An instantaneous unit sediment graph (IUSG) model is investigated for prediction of sediment yield from an upland watershed in Northwestern Mississippi. Sediment yields are predicted by convolving source runoff with an IUSG. The IUSG is the distribution of sediment from an instantaneous burst of rainfall producing one unit of runoff. The IUSG, defined as a product of the sediment concentration distribution (SCD) and the instantaneous unit hydrograph (IUH), is known to depend on the characteristics of the effective rainfall. The IUH is derived by the Nash model for each event. The SCD is assumed to be an exponential function for each event and its parameters were correlated with the effective rainfall characteristics. A sediment routing function, based on travel time and sediment particle size, is used to predict the SCD.

• 한국환경과학회지
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• 제2권1호
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• pp.29-36
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• 1993

An instantaneous unit sediment graph (IUSG) model is investigated for prediction of sediment yield from an upland watershed In Northwestern Mississippi. Sediment yields are predicted by convolving source runoff with an IUSG. The IUSG is the distribution of sediment from an instantaneous burst of rainfall producing one unit of runoff. The IUSG, defined as a product of the sediment concentration distribution (SCD) and the instantaneous unit hydrograph (IUH), is known to depend on the characteristics of the effective rainfall. The IUH is derived by the Nash model for each event. The SCD is assumed to be an exponential function for each event and its parameters were correlated with the effective rainfall characteristics. A sediment routing function, based on travel time and sediment particle size, is used to predict the SCD.