• 한국항만학회지
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• 제12권2호
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• pp.313-322
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• 1998

The distributions of chemical oxygen demand (COD) and suspended solid (SS) in Ulsan Bay were simulated and reproduced by a numerical ecosystem model for the practical application to the management of marine water quality and the prediction of water quality change due to coastal developments or the constructions of breakwater and marine facilities. Comparing the computed with the observed data of COD and SS in Ulsan bay the results of simulation were found to be good enough to satisfy the practical applications.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2009년도 춘계학술발표대회 논문집
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• pp.184-189
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• 2009

In order to improve the operation of energy systems, it is necessary for the urban communities to have reliable optimization routines, both computerized and manual, implemented in their organizations. However, before a production plan for the energy system units can be constructed, a prediction of the energy systems first needs to be determined. So, several methodologies have been proposed for energy demand prediction, but due to uncertainties in urban community, many of them will fail in practice. The main topic of this paper has been the development of a method for energy demand prediction at urban community. Energy demand prediction is important input parameters to plan for the energy planing. This paper presents a energy demand prediction method which estimates heat and electricity for various building categories. The method has been based on artificial neural networks(ANN). The advantage of ANN with respect to the other method is their ability of modeling a multivariable problem given by the complex relationships between the variables. Also, the ANN can extract the relationships among these variables by means of learning with training data. In this paper, the ANN have been applied in oder to correlate weather conditions, calendar data, schedules, etc. Space heating, cooling, hot water and HVAC electricity can be predicted using this method. This method can produce 10% of errors hourly load profile from individual building to urban community.

• 상하수도학회지
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• 제23권1호
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• pp.57-67
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• 2009

Under the supply-oriented policy, efficiency and rationale have not been fully considered in planning of water supply facilities in Korea. As a case, this study shows that large-size systems are suffering from overcapacity problem of water treatment plants, and thus discusses what options should be applied to deal with inefficiency. Water demand of large-size systems has suddenly decreased for the last 10 years while water demand has been often assumed to increase at a regular rate in planning of plants according to excess capacity hypothesis. This inconsistency led to a serious overcapacity. In 2006, total excess capacity of nine large-size systems was more than 1.2 times as large as maximum daily demand of total customers in Seoul. However, their options are expected to stay ex post facto. To prepare the risk of overcapacity, and draw large benefits out of the plants, the authors and other professionals in Korea should further discuss the more adaptive method for prediction of water demand, and systems integration between a large-size system and adjoining systems.

• 조명전기설비학회논문지
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• 제15권2호
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• pp.38-48
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• 2001

본 논문에서는 광역상수도 시스템의 취·송수 설비의 최적운영계획에 필수적으로 요구되는 시간 단위 용수 수요량 예측을 위하여 칼만 필터에 의한 수요 예측 모델 구축 및 배수패턴 해석 기법을 제안하고, 기존 시스템의 실 데이터를 이용하여 시뮬레이션 수행 결과 제안된 기법의 유용성이 검증되었다. 광역상수도 시스템에서 취·송수 설비의 최적운영계획 수립을 위해서는 예측 시간 범위를 최소 하루 단위 이상으로 유지해야 한다. 따라서, 제안된 기법에서는 기존의 시간별 실적데이터의 시계열에 의한 예측을 이용하는 것이 아니라 모델로부터 예측된 일 수요량에 배수패턴을 곱하여 24시간의 시간별 용수 수요량을 예측한다. 일 수요량 예측을 위한 칼만 필터 모델은 입력변수의 통계적 분석에 의해 모델 구조 최적화가 효과적으로 구현되고 배수패턴은 데이터 Granulization에 의해 얻어진다.

• 상하수도학회지
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• 제22권1호
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• pp.23-29
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• 2008

Throughout the analysis of field data from water distribution system, valid parameters were determined that can be included in the water service and design plan. This study investigates water consumption patterns to understand the variation of water-demand structures utilizing the pattern analysis of domestic purpose water. Water use data were collected by a public water resources management firm in Korea, Kwater, for 140 houses monitored during three years. Flow meters were installed at the faucet for drinking water, the shower booth, the laundry machine, bathroom sink, toilet, and garden faucet. Data was filtered using multiple physically meaningful criteria to improve analysis credibility. Mann Kendall and Spearman's Rho tests were used to carry out the analysis. Distinct factors of water consumption patterns can be determined for both increasing and decreasing trends of water use. Throughout the data analysis, the characterization of terms was classified and analyzed by the condition of the location of water-demand. Analysis of this data provide a physical basis for the parameter configuration of a reasonable design for a domestic water demand prediction model.

• 한국수자원학회논문집
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• 제45권11호
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• pp.1187-1199
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• 2012

본 연구에서는 Wavelet Transform과 Support Vector Machine (SVM)을 결합한 Hybrid 상수도 수요량 예측 모형을 개발하였다. Wavelet Transform 방법을 활용하여 다양한 스케일이 존재하는 상수도 수요량 시계열을 분해하여 단순한 형태의 시계열로 변환하는데 이용하였으며, 비선형 예측모형인 SVM은 이들 단순화된 시계열을 예측하는데 활용하여 예측성능을 극대화시키는 방안을 수립하였다. 본 연구에서는 상수도 수요량 자료에서 내재되어 있는 주기의 특성과 비선형 예측모형의 장점을 서로 연계한 해석이 가능하였으며 시각적인 검토 및 모든 통계지표에서 개선된 예측결과를 확인할 수 있었다. 특히, 기존 ARIMA 모형 계열에서 나타나는 자기예측문제를 상당부분 개선한 결과를 보여줌으로서 실질적인 수요량 예측모형으로서 활용이 가능할 것으로 판단된다.

• 제어로봇시스템학회논문지
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• 제9권7호
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• pp.489-497
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• 2003

A water management system is developed to reduce the unit cost of production in wide-area waterworks. Improving productivity in waterworks is to save power rate. We suggest a method to schedule the supply of water according to the time-varying power rate and pump control scheme. Water pipeline analysis package (SynerGEE Water) is utilized to obtain optimal pump control solution adaptation to water demand. Our evaluation results show that developed scheme is more efficient than the conventional.

• 한국물환경학회지
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• 제21권6호
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• pp.617-623
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• 2005

Forestry and agricultural land uses constitute 85% of Korea and these land uses are typically mixed in many watersheds. Biological Oxygen Demand (BOD) concentration is a primary factor for managing water qualities of the water resources in Korea. BOD loadings from diffuse sources, however, not well monitored yet. This study aims to assess BOD loadings from diffuse sources and their affecting factors to conserve quality of water resources. Event Mean Concentration (EMC) of BOD was calculated based on the monitoring data of forty rainfall events at four agricultural-forestry watersheds. Exceedence cumulative probability of BOD EMCs were plotted to show agricultural activities in a watershed impacts on the magnitude of EMCs. Prediction equation for each rainfall event was proposed to estimate BOD EMCs: $EMC_{BOD}(mg/L)=EXP(0.413+0.0000001157{\times}$(discharged runoff volume in $m^3$)+0.018${\times}$(ratio of agricultural land use to total watershed area).

• 한국수자원학회논문집
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• 제52권7호
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• pp.505-514
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• 2019

우리나라는 효율적인 수자원 관리를 위해 노력하고 있으며, 향후 지역의 문제와 물이용 현황, 특성, 지형, 기후 등을 고려한 유역을 세분화한 후 계획을 수립하는 것이 필요하다. 이에 본 연구에서는 한강 권역을 대상으로 MODSIM 모형을 활용하여 중권역과 표준유역단위 물 수급 체계를 구축하고 분석 결과를 비교하였다. 분석 결과, 49개년(1967-2015)간 발생하는 평균 물 부족량은 중권역 단위 129.98 백만$m^3$, 표준유역단위 2,229.24 백만 $m^3$으로 약 21 억$m^3$ 가량의 차이가 나타났으나 물 부족이 발생하는 시기와 물 부족 발생 공간 분포에 대한 경향은 매우 유사하게 나타났다. 이러한 원인은 중권역 단위 분석의 경우, 모든 수량을 이용할 수 있다는 가정으로 대표 자연유량 값에 대한 생활, 공업, 농업용수 수요량에 대한 물 부족량이 산정된다. 그러나, 표준유역단위 분석에서는 분할된 공급량과 수요량의 차이로 인해 본류와 이격되어 있는 지류는 가용할 수 있는 수자원량이 상대적으로 작아져 물 부족이 크게 발생하는 것으로 나타났고, 본류는 오히려 회귀수량의 파급효과로 인해 물 부족이 나타나지 않는 것으로 분석되었다. 향후, 분석 단위의 세분화 뿐만 아니라 실제 물이용체계가 모형 내 고려된다면 지역적 특성이 반영된 물수급 평가가 가능할 것으로 판단된다.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1508-1520
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• 2018

In this paper, we propose an improved model to provide users with a better long-term prediction of waterworks operation data. The existing prediction models have been studied in various types of models such as multiple linear regression model while considering time, days and seasonal characteristics. But the existing model shows the rate of prediction for demand fluctuation and long-term prediction is insufficient. Particularly in the deep running model, the long-short-term memory (LSTM) model has been applied to predict data of water purification plant because its time series prediction is highly reliable. However, it is necessary to reflect the correlation among various related factors, and a supplementary model is needed to improve the long-term predictability. In this paper, convolutional neural network (CNN) model is introduced to select various input variables that have a necessary correlation and to improve long term prediction rate, thus increasing the prediction rate through the LSTM predictive value and the combined structure. In addition, a multiple linear regression model is applied to compile the predicted data of CNN and LSTM, which then confirms the data as the final predicted outcome.