Development of an Evaluation Method for Deriving the Water Loss Reduction Factors of Water Distribution Systems: A Case Study in Korean Small and Medium Citiesopen access
- Authors
- Choi, Y.H.; Choi, T.; Yoo, D.G.; Lee, S.
- Issue Date
- Dec-2022
- Publisher
- MDPI
- Keywords
- correlation analysis; deep neural network; leakage management; multiple regression analysis; revenue water ratio; water distribution system
- Citation
- Applied Sciences (Switzerland), v.12, no.24
- Indexed
- SCIE
SCOPUS
- Journal Title
- Applied Sciences (Switzerland)
- Volume
- 12
- Number
- 24
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/30045
- DOI
- 10.3390/app122412530
- ISSN
- 2076-3417
2076-3417
- Abstract
- This study introduces a method that can evaluate the efficiency of leakage management practices and devises a formula to set leakage management goals. To develop the evaluation method for deriving leakage reduction factors, real data from small- and medium-sized cities in South Korea were collected. With the data collected, four leakage management factors (or activities) that could improve revenue water ratio or reduce leakage ratio were identified. With the leakage management factors, correlation analysis was carried out to identify the relationship between independent and dependent variables and within independent variables. Once the relationships were identified, standardization of the data using T-score conversion was carried out to scale all data with different units into similar ranges. Finally, the efficiency of leakage management actions was determined by the formulation of leakage using various data analysis approaches using multiple linear regression analysis and deep neural networks. As a result, pipe replacement was determined as an essential activity to decrease the leakage ratio or increase the revenue water ratio. In addition, annual water loss management actions of the small cities were more actively performed. Furthermore, the performance of data analysis using DNN is more appropriate in data classification, considering the characteristics of time series rather than independent data analysis. Through comparison of the above data classification approaches, the increase or decrease in the leakage ratio/revenue water ratio by the water loss management activity of local water distribution systems can be used to construct a more effective model for classification considering both local and temporal characteristics. © 2022 by the authors.
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Collections - 건설환경공과대학 > 건설시스템공학과 > Journal Articles

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