• Geomechanics and Engineering
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• 제36권5호
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• pp.441-453
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• 2024

Sinkhole subsidence and collapse is a common geohazard often formed in karst areas such as the state of Florida, United States of America. To predict the sinkhole occurrence, we need to understand the formation mechanism of sinkhole and its karst hydrogeology. For this purpose, investigating the factors affecting sinkholes is an essential and important step. The main objectives of the presenting study are (1) the development of a machine learning (ML)-based model, namely C5.0 decision tree (C5.0 DT), for the prediction of sinkhole susceptibility, which accounts for sinkhole/subsidence inventory and sinkhole contributing factors (e.g., geological/hydrogeological) and (2) the construction of a regional-scale sinkhole susceptibility map. The study area is east central Florida (ECF) where a cover-collapse type is commonly reported. The C5.0 DT algorithm was used to account for twelve (12) identified hydrogeological factors. In this study, a total of 1,113 sinkholes in ECF were identified and the dataset was then randomly divided into 70% and 30% subsets for training and testing, respectively. The performance of the sinkhole susceptibility model was evaluated using a receiver operating characteristic (ROC) curve, particularly the area under the curve (AUC). The C5.0 model showed a high prediction accuracy of 83.52%. It is concluded that a decision tree is a promising tool and classifier for spatial prediction of karst sinkholes and subsidence in the ECF area.

• 한국산림과학회지
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• 제97권2호
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• pp.140-143
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• 2008

This study compared the plywood demand prediction accuracy of econometric and vector autoregressive models using Korean data. The econometric model of plywood demand was specified with three explanatory variables; own price, construction permit area, dummy. The vector autoregressive model was specified with lagged endogenous variable, own price, construction permit area and dummy. The dummy variable reflected the abrupt decrease in plywood consumption in the late 1990's. The prediction accuracy was estimated on the basis of Residual Mean Squared Error, Mean Absolute Percentage Error and Theil's Inequality Coefficient. The results showed that the plywood demand prediction can be performed more accurately by econometric model than by vector autoregressive model.

• 해양환경안전학회지
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• 제1권1호
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• pp.95-106
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• 1995

The small-waterplane-area-twin-hull(SWATH) ship has been recognized as a promising high performance ship because of her superior seakeeping characteristics and large deck area for various operations compared to the conventional monohull ship. significant advances in analytical technics for the prediction of the ship motions, wave loads and structural responses, structural fatigue and its prediction, and hull vibration for ship motions, wave loads and structural responses, structural fatigue and its prediction, and hull vibration for SWATH ship have been much developed during the last twenty years. Based on these developments in technology an integrated computational procedures for prediction wave loads and structural responses can be used to get a accurate results. But the major problem of SWATH ship's structural design is the accurate prediction of structural responses by the maximum critical loads likely to be experienced during the life of SWATH. To get a easier and safer computational procedures and the analytical approach for determining the accurate structural responses, a case study has been presented through the project experienced.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 춘계학술대회 논문집 전력기술부문
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• pp.92-94
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• 2001

This paper investigated the real-time generator swing prediction by some researchers. And the first swing stability assessment based on EAC(Equal-Area Criterion) by using phasor measurement unit is proposed. Also we proposed the multi-swing prediction techniques, which is to estimate system parameters by using least square method / extrapolation with phasor measurement units. And the multi-swing prediction is performed with the estimated parameters. Future works are necessary to verify the proposed approaches in this paper.

• 한국산림과학회지
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• 제95권5호
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• pp.601-604
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• 2006

This study compared the accuracy of partial multivariate and vector autoregressive models for lumber demand prediction in Korea. The partial multivariate model has three explanatory variables; own price, construction permit area and dummy. The dummy variable reflected the boom of lumber demand in 1988, and the abrupt decrease in 1998. The VAR model consists of two endogenous variables, lumber demand and construction permit area with one lag. On the other hand, the prediction accuracy was estimated by Root Mean Squared Error. The results showed that the estimation by partial multivariate and vector autoregressive model showed similar explanatory power, and the prediction accuracy was similar in the case of using partial multivariate and vector autoregressive model.

• 한국콘텐츠학회논문지
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• 제4권2호
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• pp.21-27
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• 2004

도심지역 이동통신에 있어서 전파특성을 정확히 예측$.$분석하는 것은 통신 서비스영역의 결정, 최적 기지국 선정, 셀 설계 등에 있어 매우 중요한 사안이다. 이러한 분석에 있어서 사용되는 안테나의 종류, 지향각, 지형지물의 형태에 따라 변화하는 전파예측모델이 정확히 제시되어야 한다. 또한, 선택된 지역에 대하여 셀 설계를 수행하기 전에 기존에 제시된 다양한 모델 중 유사성을 가진 모델을 분석하고 그 파라미터를 측정하여 평가하는 작업을 진행하여야 한다. 본 논문에서는 도심지역의 지형 및 장애물 등을 고려한 전파예측모델을 적용하고 그에 따르는 파리미터를 추출하여 분석된 전파환경에 적용하고 그 전파특성을 분석하기 위한 시뮬레이션을 실시하였다. 이러한 과정을 통하여 우리는 주어진 전파환경에 적절한 기지국의 위치, 지형고도 안테나의 종류 및 높이 등 핵심적인 파라미터들을 원하는 정확도로 추출하였다.

• Nuclear Engineering and Technology
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• 제52권11호
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• pp.2471-2478
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• 2020

Pumps are essential machinery in the various industries. With the development of high-speed and large-scale pumps, especially high energy density, high requirements have been imposed on the vibration and noise performance of pumps, and cavitation is an important source of vibration and noise excitation in pumps, so it is necessary to improve pumps cavitation performance. The modern pump optimization design method mainly adopts parameterization and artificial intelligence coupling optimization, which requires direct correlation between geometric parameters and pump performance. The existing cavitation performance calculation method is difficult to be integrated into multi-objective automatic coupling optimization. Therefore, a fast prediction method for pump cavitation performance is urgently needed. This paper proposes a novel cavitation prediction method based on impeller pressure isosurface at single-phase media. When the cavitation occurs, the area of pressure isosurface S_iso increases linearly with the NPSH_a decrease. This demonstrates that with the development of cavitation, the variation law of the head with the NPSH_a and the variation law of the head with the area of pressure isosurface are consistent. Therefore, the area of pressure isosurface S_iso can be used to predict cavitation performance. For a certain impeller blade, since the area ratio R_s is proportional to the area of pressure isosurface S_iso, the cavitation performance can be predicted by the R_s. In this paper, a new cavitation performance prediction method is proposed, and the feasibility of this method is demonstrated in combination with experiments, which will greatly accelerate the pump hydraulic optimization design.

• 한국유체기계학회 논문집
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• 제10권5호
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• pp.41-45
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• 2007

The effects of channel area on the performance of regenerative type fuel pump were numerically studied by commercial CFD code (ANSYS CFX-10). To examine the effects of channel area, the shapes of the side channel and blade were simplified. The channel area affected the flow characteristics of the internal recirculation flow between the side channel and the blade groove and also made a difference in the overall performance. These loss mechanism with circulation flow were adopted as a loss coefficient in the performance prediction program. The loss coefficient was newly derived from the results of calculations with different channel area, and compared with the experimental results in the reference paper and used to modify the performance prediction program. The circulation flow characteristics with different channel area, which is related with loss mechanism, were also discussed with the results of 3-dimensional flow calculations.

• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.885-893
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• 2013

This paper considers Bayes estimations of the small area means under Fay-Herriot model with measurement errors. We provide empirical Bayes predictors of small area means with the corresponding jackknifed mean squared prediction errors. Also we obtain hierarchical Bayes predictors and the corresponding posterior standard deviations using Gibbs sampling. Numerical studies are provided to illustrate our methods and compare their eciencies.

• 한국지리정보학회지
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• 제14권4호
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• pp.116-127
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• 2011

본 논문에서는 로지스틱 회귀분석 기법을 이용하여 산사태 취약성 분석을 수행하였다. 예측모델의 성능은 모델의 적합도 검증을 통해 사용된 데이터가 모델에 얼마나 잘 반영되어 구축되었는지에 대한 적합도 평가뿐만 아니라 예측성능에 대한 평가가 필요하다. 따라서 이 논문에서는 모델에 대한 객관적인 결과를 얻기 위해 이와 같은 두 가지 측면에 대하여 예측성능 평가를 적용하였다. 연구지역은 2006년도 집중 호우로 많은 산사태가 발생한 강원도 인제 일대를 대상으로 하였다. 산사태 관련인자들은 지형도, 토양도, 임상도로부터 추출하였다. 예측모델에 대한 평가는 누적이득차트 곡선의 하부영역을 계산하였다. 예측모델의 적합도 평가에서는 87.9% 교차검증을 통한 예측정확도 평가 결과 84.8%로 두 평가 결과간의 큰 차이를 보이지 않으며 좋은 성능의 결과를 산출하였다. 이는 산사태와 관련성이 높은 유발인자와 예측모델 성능에서 기인된 결과로 해석 될 수 있다.