• 한국수자원학회논문집
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• 제38권1호
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• pp.11-23
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• 2005

본 연구에서는 단기 예측강우를 활용하여 실시간 유량을 예측할 수 있는 기상-수자원 연계기법을 개발하였다. 이를 위해 기상청의 RDAPS 강수자료와 저류함수(SFM) 모델을 통해 소양강댐 상류유역의 댐유입량을 계산하고 그 정확도를 분석하였다. 대상 사례기간인 2003년 7월 18일부터 2003년 7월 24일까지 RDAPS 강우예측자료의 정확도를 평가한 결과 RDAPS 및 관측 강수량 사이의 정성적 평가에서 매우 우수한 정확도를 보이고, 수자원 측면에서 필요한 정량적 성격을 충족시키는 것으로 나타났다. RDAPS-SFM 연계기법을 통한 하천유량 계산에서도 그 정확도가 비교적 높은 것으로 검토되어 현재의 하천 유량 예측에서 기상 수치예보자료의 활용성은 매우 높은 것으로 사료된다.

• 설비공학논문집
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• 제25권6호
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• pp.310-316
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• 2013

This study was designed to investigate a method for short-term, real-time energy demand prediction, to cope with changing loads for the effective operation and management of buildings. Through a case study, a novel methodology for real-time energy demand prediction with the use of weather forecasting data was suggested. To perform the input and output operations of weather data, and to calculate solar radiation and EnergyPlus, the BCVTB (Building Control Virtual Test Bed) was designed. Through the BCVTB, energy demand prediction for the next 24 hours was carried out, based on 4 real-time weather data and 2 solar radiation calculations. The weather parameters used in a model equation to calculate solar radiation were sourced from the weather data of the KMA (Korea Meteorological Administration). Depending on the local weather forecast data, the results showed their corresponding predicted values. Thus, this methodology was successfully applicable to anywhere that local weather forecast data is available.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 추계 학술발표회
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• pp.253-262
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• 2010

In this study, localized heavy rainfall occurred during the collapse of steep slopes adjacent to the construction site and to ensure the safety of residents to build an early warning system was performed. Forecast/Alert range was estimated based on vulnerability landslide map and past disaster history. And established a critical line in consideration of the characteristics of local rainfall and operating a snake line, the study calculated causing and non-causing points. Also, be measured in real-time analysis of rainfall data in conjunction with the system before the steep slope failure occurred forecast/Alert System is presented.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권4호
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• pp.305-312
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• 2014

This paper discusses real-time peak shaving algorithms for a large-scale battery energy storage system (BESS). Although several transmission and distribution functions could be implemented for diverse purposes in BESS applications, this paper focuses on a real-time peak shaving algorithm for an energy time shift, considering wind power generation. In a high wind penetration environment, the effective load levels obtained by subtracting the wind generation from the load time series at each long-term cycle time unit are needed for efficient peak shaving. However, errors can exist in the forecast load and wind generation levels, and the real-time peak shaving operation might require a method for wind generation that includes comparatively large forecasting errors. To effectively deal with the errors of wind generation forecasting, this paper proposes a real-time peak shaving algorithm for threshold value-based peak shaving that considers fuzzy wind power generation.

• 한국농공학회논문집
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• 제59권2호
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• pp.69-79
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• 2017

In this study, we developed real-time urban stream discharge forecasting model using short-term rainfall forecasts data simulated by a regional climate model (RCM). The National Centers for Environmental Prediction (NCEP) Climate Forecasting System (CFS) data was used as a boundary condition for the RCM, namely the Global/Regional Integrated Model System(GRIMs)-Regional Model Program (RMP). In addition, we make ensemble (ESB) forecast with different lead time from 1-day to 3-day and its accuracy was validated through temporal correlation coefficient (TCC). The simulated rainfall is compared to observed data, which are automatic weather stations (AWS) data and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA 3B43; 3 hourly rainfall with $0.25^{\circ}{\times}0.25^{\circ}$ resolution) data over midland of Korea in July 26-29, 2011. Moreover, we evaluated urban rainfall-runoff relationship using Storm Water Management Model (SWMM). Several statistical measures (e.g., percent error of peak, precent error of volume, and time of peak) are used to validate the rainfall-runoff model's performance. The correlation coefficient (CC) and the Nash-Sutcliffe efficiency (NSE) are evaluated. The result shows that the high correlation was lead time (LT) 33-hour, LT 27-hour, and ESB forecasts, and the NSE shows positive values in LT 33-hour, and ESB forecasts. Through this study, it can be expected to utilizing the real-time urban flood alert using short-term weather forecast.

• 산업경영시스템학회지
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• 제41권2호
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• pp.9-15
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• 2018

This study is intended to investigate that it is possible to analyze the public awareness and satisfaction of the weather forecast service provided by the Korea Meteorological Administration (KMA) through social media data as a way to overcome limitations of the questionnaire-based survey in the previous research. Sentiment analysis and association rule mining were used for Twitter data containing opinions about the weather forecast service. As a result of sentiment analysis, the frequency of negative opinions was very high, about 75%, relative to positive opinions because of the nature of public services. The detailed analysis shows that a large portion of users are dissatisfied with precipitation forecast and that it is needed to analyze the two kinds of error types of the precipitation forecast, namely, 'False alarm' and 'Miss' in more detail. Therefore, association rule mining was performed on negative tweets for each of these error types. As a result, it was found that a considerable number of complaints occurred when preventive actions were useless because the forecast predicting rain had a 'False alarm' error. In addition, this study found that people's dissatisfaction increased when they experienced inconveniences due to either unpredictable high winds and heavy rains in summer or severe cold in winter, which were missed by weather forecast. This study suggests that the analysis of social media data can provide detailed information about forecast users' opinion in almost real time, which is impossible through survey or interview.

• 대기
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• 제25권1호
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• pp.1-18
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• 2015

The most objective way to overcome the limitation of numerical weather prediction model is to represent the uncertainty of prediction by introducing probabilistic forecast. The uncertainty of the numerical weather prediction system developed due to the parameterization of unresolved scale motions and the energy losses from the sub-scale physical processes. In this study, we focused on the growth of model errors. We performed ensemble forecast to represent model uncertainty. By employing the multi-physics scheme (PHYS) and the stochastic kinetic energy backscatter scheme (SKEBS) in simulating typhoon Rusa (2002), we assessed the performance level of the two schemes. The both schemes produced better results than the control run did in the ensemble mean forecast of the track. The results using PHYS improved by 28% and those based on SKEBS did by 7%. Both of the ensemble mean errors of the both schemes increased rapidly at the forecast time 84 hrs. The both ensemble spreads increased gradually during integration. The results based on SKEBS represented model errors very well during the forecast time of 96 hrs. After the period, it produced an under-dispersive pattern. The simulation based on PHYS overestimated the ensemble mean error during integration and represented the real situation well at the forecast time of 120 hrs. The displacement speed of the typhoon based on PHYS was closest to the best track, especially after landfall. In the sensitivity tests of the model uncertainty of SKEBS, ensemble mean forecast was sensitive to the physics parameterization. By adjusting the forcing parameter of SKEBS, the default experiment improved in the ensemble spread, ensemble mean errors, and moving speed.

• 상하수도학회지
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• 제19권6호
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• pp.738-748
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• 2005

Considering pollution source is transferred by discharge, it is very important to analyze the correlation between discharge and water quality. And temperature also influent to the water quality. In this paper, it is used water quality data that was measured DO (Dissolved Oxygen), TOC (Total Organic Carbon), TN (Total Nitrogen), TP (Total Phosphorus) at Dalchun real time monitoring stations in Namhan river. These characteristics were analyzed with the water quality of rainy and nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water quality forecasting models were applied. LMNN (Levenberg-Marquardt Neural Network), MDNN (MoDular Neural Network), and ANFIS (Adaptive Neuro-Fuzzy Inference System) models have achieved the highest overall accuracy of TOC data. LMNN and MDNN model which are applied for DO, TN, TP forecasting shows better results than ANFIS. MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. If some data has periodical properties, it seems effective using qualitative data to forecast.

• 한국수자원학회논문집
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• 제38권12호
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• pp.1061-1072
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• 2005

본 연구에서는 영산호의 상류에 위치한 나주유역의 홍수시 유출량을 실시간으로 예측하기 위하여 Grey홍수 유출모형을 개발하였다. 나주유역의 유출량은 나주수위관측소에서 실시간으로 측정하고 있으며, 이곳은 영산호의 유입홍수량을 예측과 홍수관리를 위한 주관측소이다. 모형의 지배방정식은 Grey시스템 이론에 근거하여 구성되었으며, 모형의 매개변수는 Grey 시스템매개변수의 조합으로 구성하였다. 모형의 차수는 실측자료와 모의결과를 비교하여 다른 차수 보다 양호한 결과를 나타내는 5차로 하였다. 모형의 보정시 예측결과와 실측치간의 RMSE는 $3.1\~290.5m^{3}/sec$를 나타냈으며, $R^{2}$는 $0.909\~0.999$를 나타냈다. 모형의 검정시 예측결과와 실측치간의 RMSE는 $20.6\~147.4m^{3}/sec$를 나타냈으며, $R^{2}는\;0.940\~0.998$를 나타냈다. 매개변수가 추정된 모형을 이용하여 담수호의 유입량을 하천수위 상태에 따라 예측한 결과, 하천수위가 상승할 경우와 하강할 경우의 예측 홍수량은 예측시간이 증가할수록 커지는 경향을 나타냈다. 또한, 하천수위가 첨두에 가까운 시기의 홍수량은 예측시간에 관계없이 실측자료와 비슷한 결과를 나타냈다. 이와 같은 결과는 Grey 홍수유출모형을 홍수시 담수호 유입량을 실시간으로 정확하게 예측하는데 적용할 수 있음을 나타낸다.

• 한국지리정보학회지
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• 제21권3호
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• pp.76-92
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• 2018

본 연구는 상습적으로 도시침수 피해를 입은 지역을 대상으로 도시 홍수 예 경보를 위한 강우 시나리오별 사전 침수면적 데이터베이스를 구축하고 강우강도에 따른 침수예상도를 작성하여 기상청 최대강우량 예보와 함께 홍수위험지역을 사전에 예보할 수 있는 방법을 제안하고자 한다. 데이터베이스 구축을 위하여 1D-2D 모형 구축을 실시하고 실제호우사상에 대한 검증을 완료한 다음 시나리오별 해석을 실시하였다. 2010년 9월 21일에 대상유역에 내린 강우사상에 대한 2D 해석결과를 NDMS 자료와 비교 분석 하였다. NDMS 신고지점은 총 118지점에서 신고가 되었으며, 2D 침수해석 결과 82개 지점이 계산결과에 포함되었다. NDMS 신고 지점과 2D 침수해석 결과에 대하여 적합도를 계산한 결과 69.5%의 적합도로 분석되었다. 사전 침수 데이터베이스를 이용하여 침수예상도를 작성하였으며, 70mm의 침수예상도의 경우 NDMS 신고 지점과 70.3%의 적합도를 가졌으며, 80mm의 침수예상도의 경우 72.0%의 적합도를 가지는 것으로 분석되었다. 구축된 사전 침수면적 데이터베이스를 이용하여 기상예보와 함께 침수예상도 정보를 함께 제시할 수 있으며 침수 예 경보 시 선행시간을 확보할 수 있다.