• 대한전기학회논문지:전력기술부문A
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• 제51권3호
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• pp.109-117
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• 2002

High accuracy of the load forecasting for power systems improves the security of the power system and generation cost. However, the forecasting problem is difficult to handle due to the nonlinear and the random-like behavior of system loads as well as weather conditions and variation of economical environments. So far. many studies on the problem have been made to improve the prediction accuracy using deterministic, stochastic, knowledge based and artificial neural net(ANN) method. In the conventional load forecasting method, the load forecasting maximum error occurred for the holidays on Saturday and Monday. In order to reduce the load forecasting error of the daily peak load for the holidays on Saturday and Monday, fuzzy concept and linear regression theory have been adopted into the load forecasting problem. The proposed algorithm shows its good accuracy that the average percentage errors are 2.11% in 1996 and 2.84% in 1997.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.1194-1201
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• 2022

The existing literature has witnessed the importance of productivity assessment and deducing factors affecting it. However, yet many models have shown limitations in practical applications in actual construction sites for process planning due to uncertainty and lack of data. This research presents a productivity assessment and database generation framework using simulation and compares the results with RSMeans to derive appropriate equipment combinations alternatives for earthwork operations. Data of 15 different conditions was collected from 5 different construction sites. Prediction accuracy above 90% were achieved for the simulation models with average error rate of 7.4%. The construction productivity assessment framework presented in this study is expected to be highly applicable to operation planning for earthwork operations.

• 산업기술연구
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• 제43권1호
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• pp.57-62
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• 2023

In this review, we introduce the non-parametric Bayesian filtering algorithm known as the point-mass filter (PMF) and discuss recent studies related to it. PMF realizes Bayesian filtering by placing a deterministic grid on the state space and calculating the probability density at each grid point. PMF is known for its robustness and high accuracy compared to other nonparametric Bayesian filtering algorithms due to its uniform sampling. However, a drawback of PMF is its inherently high computational complexity in the prediction phase. In this review, we aim to understand the principles of the PMF algorithm and the reasons for the high computational complexity, and summarize recent research efforts to overcome this challenge. We hope that this review contributes to encouraging the consideration of PMF applications for various systems.

• 대한기계학회논문집A
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• 제37권7호
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• pp.921-927
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• 2013

본 연구는 운용 파라미터의 불확실성을 고려한 착륙장치 완충성능 해석 기법을 제시한다. 실제 운용 환경에서 완충성능에 영향을 미치는 많은 파라미터는 어느 정도의 불확실성을 가지게 되는데, 완충장치 가스 압력과 오일 체적, 타이어 압력, 외부 온도 등을 예로 들 수 있다. 본 연구에서는 Convex Modeling 과 Interval Analysis 기법을 적용하여, 이러한 불확실성이 착륙 시의 지면 반력에 미치는 효과를 해석하였다. 불확실한 파라미터를 고려할 경우, 완충효율 및 구조 건전성에 중요한 영향을 주는 Peak load 가 Deterministic analysis 의 결과보다 크게 증가하였다. 안전성과 신뢰성의 확보를 위해서는 이러한 불확실성을 반영하는 것이 필요하며, 제시한 방법은 이를 효율적으로 처리할 수 있음을 보여준다.

• Geomechanics and Engineering
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• 제30권2호
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• pp.187-199
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• 2022

Kriging metamodel, as a flexible machine learning method for approximating deterministic analysis models of an engineering system, has been widely used for efficiently estimating slope reliability in recent years. However, the autocorrelation function (ACF), a key input to Kriging that affects the accuracy of reliability estimation, is usually selected based on empiricism. This paper proposes an adaption of the Kriging method, named as Genetic Algorithm optimized Whittle-Matérn Kriging (GAWMK), for addressing this issue. The non-classical two-parameter Whittle-Matérn (WM) function, which can represent different ACFs in the Matérn family by controlling a smoothness parameter, is adopted in GAWMK to avoid subjectively selecting ACFs. The genetic algorithm is used to optimize the WM model to adaptively select the optimal autocorrelation structure of the GAWMK model. Monte Carlo simulation is then performed based on GAWMK for a subsequent slope reliability analysis. Applications to one explicit analytical example and two slope examples are presented to illustrate and validate the proposed method. It is found that reliability results estimated by the Kriging models using randomly chosen ACFs might be biased. The proposed method performs reasonably well in slope reliability estimation.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2010년도 춘계학술대회 논문집
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• pp.49-49
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• 2010

The most commonly used numerical modelling techniques for acoustics and vibration are based on element based techniques, such as the nite element and boundary element method. Due to the huge computational eorts involved, the use of these deterministic techniques is practically restricted to low-frequency applications. For high-frequency modelling, probabilistic techniques such as SEA are well established. However, there is still a wide mid-frequency range, for which no adequate and mature prediction techniques are available. In this frequency range, the computational eorts of conventional element based techniques become prohibitively large, while the basic assumptions of the probabilistic techniques are not yet valid. In recent years, a vast amount of research has been initiated in a quest for an adequate solution for the current midfrequency problem. One family of research methods focuses on novel deterministic approaches with an enhanced convergence rate and computational eciency compared to the conventional element based methods in order to shift the practical frequency limitation towards the mid-frequency range. Amongst those techniques, a wave based prediction technique using an indirect Tretz approach is being developed at the K.U.Leuven - Noise and Vibration Research group. This paper starts with an outline of the major features of the mid-frequency modelling challenge and provides a short overview of the current research activities in response to this challenge. Next, the basic concepts of the wave based technique and its hybrid coupling with nite element schemes are described. Various validations on two- and threedimensional acoustic, elastic, poro-elastic and vibro-acoustic examples are given to illustrate the potential of the method and its benecial performance as compared to conventional element based methods. A closing part shares some views on the open issues and future research directions.

• 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.

• 대한토목학회논문집
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• 제38권5호
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• pp.671-683
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• 2018

도시유역에 대한 집중호우에 따른 침수피해가 증가하고 있으며, 기존에 수행된 많은 연구에서 입증 되어진 바와 같이 도시 침수는 하수관망의 통수능을 상회함에 따라 발생하는 내수침수에 주로 기인하고 있다. 도시화가 상당히 진행되고 인구가 밀집되어 있는 지역에 대한 침수피해는 심각한 사회 경제적 피해를 야기한다. 이에 따라 도시지역에 대한 홍수 예측을 위한 확정 및 확률론적 연구가 진행되어 왔지만, 충분한 선행시간을 확보하며 단시간에 홍수량에 대한 예측결과를 도출하기에는 부족한 실정이다. 본 연구에서는 최적의 실시간 도시 홍수 예측 기법을 제시하기 위하여 도시유출해석 기반 실시간 홍수 예측을 위한 IDNN, TDNN 그리고 NARX 동적신경망을 비교하였다. 강남 지역의 2010, 2011년 실제 호우사상에 대하여 총 홍수량 예측 결과, 입력 지연 인공신경망의 최대 Nash-Sutcliffe 효율 계수는 각각 0.86, 0.53, 시간 지연 인공신경망의 경우 0.92, 0.41, 외생변수를 이용한 비선형 자기 회귀의 경우 0.99, 0.98으로 나타났다. 연구 대상지역에 대한 각 맨홀 누적월류량을 고려한 예측 결과의 오차분석을 통하여 외생변수를 이용한 비선형 자기 회귀 기법을 사용하는 것이 추후 도시 홍수 대응체계 구축에 적합할 것으로 나타났다.

• 한국구조물진단유지관리공학회 논문집
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• 제8권2호
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• pp.159-167
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• 2004

콘크리트의 압축강도는 콘크리트를 생산하는 기준으로 사용된다. 콘크리트 압축강도 시험은 복잡하고 시간이 걸리는 일이고, 보통 건설현장에서 타설 후 28일 후에 실행되기 때문에, 시험결과가 필요강도를 만족하지 않을 경우에 구조물의 시공에 문제를 초래할 수도 있다. 따라서, 콘크리트 타설 전에 강도를 예측하는 것이 요구되고 있다. 본 연구에서는 콘크리트 배합비를 기초로 하여 콘크리트 압축강도를 예측하기 위한 확률론적 방법을 제시하였다. 패턴인식 분야에서 많이 활용되어온 확률신경망 기법을 활용하여 콘크리트 압축강도 추정을 수행하였다. 콘크리트 압축강도 시험결과를 활용하여 확률신경망 기법의 적용성을 검증하였으며, 실제 시험결과와 비교를 수행하였다. 비교결과, 본 연구에서 제시된 확률신경망을 활용한 콘크리트 압축강도 추정기법이 콘크리트의 압축강도를 확률적으로 추정하는데 매우 효과적으로 적용될 수 있음을 확인하였다.

• 한국통신학회논문지
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• 제24권12A호
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• pp.1974-1984
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• 1999

본 논문은 정확한 전파 모델과 신속한 전파 예측 모델을 필요로 하는 다중 경로 현상을 효과적으로 획득하기 위해 효율적인 데이터 표현 구조를 제안한다. 본 논문은 ray tracing에서 사용되고 있는 VR(Vector Representation)을 향상시키기 위한 데이터 표현 구조로서, 빌딩과 같은 오브젝트를 표현하기 위해 CR(Circular Representation)을 이용하는 오브젝트 표현 방법을 제안한다. 제안된 CR은 건물의 중심에서 건물을 둘러싸도록 원을 그리는 형태이다. 본 구성에서 CR은 기하학적 구조를 위한 기본 빌딩 구조로서의 기능을 가지며, VR이 단독으로 사용되어 졌을 때 보다 더 많은 효율성을 증진시킨다. VR은 건물을 표현하기 위해 여러 개의 벽면 벡터를 필요로 하는 반면, CR은 하나의 원으로 표현된다. 결과적으로 제안된 방법에 의해 ray tracing에서 상당한 양의 계산 비용을 줄일 수 있다. 본 논문의 목표는 효율적인 ray tracing 예측 모델을 위해 데이터 구조화 시에 효율성을 얻기 위한 해결책으로서 CR을 제안하는 것이다. 본 논문은 제안된 방법에 의해 계산 부하량이 현저하게 줄어듬을 보인다. 또한 deterministic ray tracing 모델에서 CR의 계층? 구조의 수반 가능한 사용을 보인다. 시뮬레이션 결과는 계층적 octree 구조가 약 50% 계산 부하를 감소시키고 있는 반면 본 논문에서 제안된 CR은 분산된 물체의 수에 비례하여 계산 부하량을 현저하게 감소시킨다는 것을 나타낸다.