• Membrane and Water Treatment
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• 제12권2호
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• pp.65-73
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• 2021

Sponge ball cleaning can generate an abrasion effect, which leads to an attractive increasing in both permeate flux and membrane rejection. The aim of this study was to investigate the influence of the daily sponge ball cleaning (SBC) on the performance of different UF cross-flow membrane modules integrated with a bioreactor. Two 1"-membrane modules and one 1/2"-membrane module were tested. The parameters measured and controlled are temperature, pH, viscosity, particle size, dissolved organic carbon (DOC), total suspended solids (TSS), and permeate flux. The permeate flux could be improved by 60%, for some modules, after 11 days of daily sponge ball cleaning at a transmembrane pressure of 350 kPa and a flow velocity of 4 m/s. Rejection values of all tested modules were improved by 10%. The highest permeate flux of 195 L/㎡.h was achieved using a 1"-membrane module with the aid of its negatively charged membrane material and the daily sponge ball cleaning. In addition, the enhancement in the permeate flux caused by daily sponge ball cleaning improved the energy specific demand for all tested modules. The negatively charged membrane showed the lowest energy specific demand of 1.31 kWh/㎥ in combination with the highest flux, which is a very competitive result.

• 산업공학
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• 제24권4호
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• pp.373-378
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• 2011

High level of accuracy in forecasting heat demand of each district is required for operating and managing the district heating efficiently. Heat demand has a close connection with the demands of the previous days and the temperature, general demand forecasting methods may be used forecast. However, there are some exceptional situations to apply general methods such as the exceptional low demand in weekends or vacation period. We introduce a new method to forecast the heat demand to overcome these situations, using the linearities between the demand and some other factors. Our method uses the temperature and the past 7 days' demands as the factors which determine the future demand. The model consists of daily and hourly models which are multiple linear regression models. Appling these two models to historical data, we confirmed that our method can forecast the heat demand correctly with reasonable errors.

• 한국농공학회지
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• 제30권2호
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• pp.95-104
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• 1988

This study refers to the development of a hydrologic model simulating daily inflow and release rates for inigation reservoirs. A daily - based model is needed for adequate operation of an irrigation reservoir sufficing the water demand for paddy fields which is closely related to meteorological conditions. And the objective of this study is to develop a reservoir release rate model and then to calibrata the parameters. The release rates model considers daily water demands , water supply for transplanting, minmum release for maintaining canal flow, and maxirnun and regular flooding depth for determining effective rainfall on paddy fields. Each of the factors in the model was regarded as a lumped pararuter representing the average condition of a whole irrigated area. The water demand was estimated form the potential evapotranspiration by Penman method, the effective rainfall, and the infiltration on paddy fields. The release model was found to be capable of adequately simulating daily reservoir releases based on meteorological data.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2003년도 학술발표논문집
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• pp.495-498
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• 2003

In order to analyze water supply capacity in estuary barrage dam, a system was developed in which base model was consisted of daily water balance model and daily inflow model. Agricultural water demand to paddy fields and domestic and industrial water demand were considered in this daily water balance model. Also outflow volume through sluice gate and inside water level at time to start outflow was conditioned initially to simulate reservoir storage. The DAWAST model was selected to simulate daily reservoir inflow in which return flows from agricultural, domestic and industrial water were included to simulate runoff. Using this developed system, water supply capacity in the Keum river estuary reservoir was analyzed.

• 농촌계획
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• 제15권1호
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• pp.61-71
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• 2009

The objective of this research was to analyze the determinants of demand for residential settlements in rural societies. A significant aspect of the demand analysis was to consider depopulation classification as a moderating variable with a view to its role as an essential dividing factor of socioeconomic characteristics and physical environments of the areas of concern. The data collection for analysis was divided according to types of depopulation into the three categories of less developed, stagnated, and developed areas. For the cause and effect analysis between the residential demand and factors of settlement, the ordered probit model was applied. Significant determinants of settlement demand unfolded according to depopulation types. In the case of less developed areas, residential demand was affected significantly by the factors of daily life convenience and public facilities. Key settlement demand determinants of stagnated regions included the aspects of basic natural environment, daily life convenience and education. Meanwhile, key settlement demand determinants for developed areas included education and agriculture economic aspects. The importance-performance analysis was also applied to a set of settlement characteristics of rural communities to figure out the settlement factors requiring urgent endeavor to improve.

• Journal of the Korean Data and Information Science Society
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• 제28권2호
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• pp.395-406
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• 2017

전력 공급 시스템의 효율적인 운영을 위해 전력수요예측은 필수적이다. 본 연구에서는 군집분석과 분류분석을 이용하여 일 단위 시간별 전력수요량 시계열 패턴의 유형을 살펴보고자 한다. 전력거래소에서 수집된 2008년 1월 1일부터 2012년 12월 31일까지의 일 단위 시간별 전력수요량 데이터를 추세성분, 계절성분, 오차 성분으로 구성된 시계열 자료로 변환하여 사용하였다. 추세성분을 제거한 시계열 자료의 패턴을 구분하기 위한 군집 분석방법은 k-평균 군집분석 (k-means), 가우시안혼합모델 혼합 모델 군집분석 (Gaussian mixture model), 함수적 군집분석 (functional clustering)을 고려하였다. 주성분분석을 통해 24시간 자료를 2개의 요인로 축소한 후 k-평균 군집분석과 가우시안 혼합 모델, 함수적 군집분석을 수행하였다. 군집분석 결과를 토대로 2008년부터 2011년까지 총 4년간 데이터를 4가지 분류분석방법인 의사결정나무, RF (random forest), Naive bayes, SVM (support vector machine)을 통해 훈련시켜 2012년 군집을 예측하였다. 분석 결과 가우시안 혼합 분포기반 군집분석과 RF를 이용한 군집예측 결과의 성능이 가장 우수하였다.

• 상하수도학회지
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• 제12권4호
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• pp.43-52
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• 1998

The purpose of this study is to establish a method of estimating the daily urban water demend using Backpropagation algorithm is part of ANN(Artificial Neural Network). This method will be used for the development of the efficient management and operations of the water supply facilities. The data used were the daily urban water demend, the population and weather conditions such as treperarture, precipitation, relative humidity, etc. Kwangju city was selected for the case study area. We adjusted the weights of ANN that are iterated the training data patterns. We normalized the non-stationary time series data [-1,+1] to fast converge, and choose the input patterns by statistical methods. We separated the training and checking patterns form input date patterns. The performance of ANN is compared with multiple-regression method. We discussed the representation ability the model building process and the applicability of ANN approach for the daily water demand. ANN provided the reasonable results for time series forecasting.

• 응용통계연구
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• 제26권2호
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• pp.349-360
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• 2013

최근 일별 최대 전력수요 예측은 전력설비 계획 및 운용에 매우 중요한 사안으로 주목받고 있다. 본 연구는 일별 최대 전력수요 예측을 위하여 대표적 시계열 모형을 소개하고, 예측의 성능 비교를 위하여 RMSE(Root mean squared error)와 MAPE(Mean absolute percentage error)를 사용한다. 연구결과로 보완된 Holt-Winters 모형과 Reg-ARIMA 모형이 다른 모형에 비하여 우수한 예측 성능을 보였다.

• 한국농공학회지
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• 제43권1호
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• pp.53-65
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• 2001

To estimate agricultural water demand, many factors such as weather, crops, soil, cultivation method, crop coefficient and cultivation area, etc. must be considered. But it is not easy to estimate water demand in consideration of these factors, which are variable according to growth stage and regional environment. This study provides estimation system for agricultural water demand(ESAD) in order to estimate water demand easily and accurately, and arranges all factors needed for water demand estimation. This study identifies the application of estimation system for agricultural water demand with the data observed in the other studies, and analyzes nationwide agricultural water demand. The results are as follows. 1) The practice of different rice cultivation in the paddy field resulted in different water demands. Water depth and infiltration ratio in paddy are the most important factors to estimate water demand. The water depths in paddy simulated by ESAD is very similar to the observed ones. 2) Water demand of upland crops varies with the crops, soil, etc.. Effective rainfall estimated by daily routing of soil moisture varies according to the crops, soil, and effective soil zone(root depth). As crop root become grown, effective rainfall and an amount of irrigation water has been increased. 3) The current unit water demand of upland crops applied as 500mm or 550mm to estimate water demand does not reflect the differences caused by the crops, regional surrounding, weather condition, etc. Results from ESAD for the estimation of water demand of upland crops show that ESAD can simulate the actual field conditions reasonably because it simulates the actual irrigation practices with the daily routing of soil moisture.

• 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.