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인구통계학적 요인 및 원격검침 자료를 활용한 가정용 물 사용패턴 분류 및 물 사용량 예측 연구 KCI 등재

Water consumption forecasting and pattern classification according to demographic factors and automated meter reading

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  • URLhttps://db.koreascholar.com/Article/Detail/415488
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상하수도학회지 (Journal of the Korean Society of Water and Wastewater)
대한상하수도학회 (Korean Society Of Water And Wastewater)
초록

The water consumption data of individual consumers must be analyzed and forecast to establish an effective water demand management plan. A k-mean cluster model that can monitor water use characteristics based on hourly water consumption data measured using automated meter reading devices and demographic factors is developed in this study. In addition, the quantification model that can estimate the daily water consumption is developed. K-mean cluster analysis based on the four clusters shows that the average silhouette coefficient is 0.63, also the silhouette coefficients of each cluster exceed 0.60, thereby verifying the high reliability of the cluster analysis. Furthermore, the clusters are clearly classified based on water usage and water usage patterns. The correlation coefficients of four quantification models for estimating water consumption exceed 0.74, confirming that the models can accurately simulate the investigated demographic data. The statistical significance of the models is considered reasonable, hence, they are applicable to the actual field. Because the use of automated smart water meters has become increasingly popular in recent year, water consumption has been metered remotely in many areas. The proposed methodology and the results obtained in this study are expected to facilitate improvements in the usability of smart water meters in the future.

목차
ABSTRACT
1. 서 론
2. 연구방법 및 내용
    2.1 연구대상지역 상수도 원격검침 자료 조사 및 결측자료 보정
    2.2 연구대상지역 인구통계학적 요인 조사
    2.3 물 사용 특성 분류를 위한 k-평균 군집분석(k-meanclustering)
    2.4 인구통계학적 특성에 따른 lpcd 예측을 위한 수량화분석
3. 연구결과 및 고찰
    3.1 상수도 원격검침 자료 분석
    3.2 인구통계학적 특성과 물사용량 사이 관계 분석
    3.3 k-평균 군집분석을 활용한 물 사용 패턴 분류
    3.4 인구통계학적 특성을 고려한 lpcd 추정 결과
4. 결 론
사 사
References
저자
  • 김기범(Division of Construction Engineering and Management, Purdue University) | Kibum Kim
  • 박해금(서울시립대학교 환경공학과) | Haekeum Park (Department of Environmental Engineering, University of Seoul)
  • 김태현(서울시립대학교 환경공학과) | Taehyeon Kim (Department of Environmental Engineering, University of Seoul)
  • 형진석(서울시립대학교 환경공학과) | Jinseok Hyung (Department of Environmental Engineering, University of Seoul.)
  • 구자용(서울시립대학교 환경공학과) | Jayong Koo (Department of Environmental Engineering, University of Seoul.) Corresponding author