A review on current technologies and future direction of water leakage detection in water distribution network

MR Islam, S Azam, B Shanmugam, D Mathur - IEEE Access, 2022 - ieeexplore.ieee.org
Water leakage in the supply system is a silent problem that costs billions of dollars yearly. As
these supply pipes are mostly underground, this leakage remains undetected for a long …

[HTML][HTML] Addressing data limitations in leakage detection of water distribution systems: Data creation, data requirement reduction, and knowledge transfer

Y Wu, S Liu, Z Kapelan - Water Research, 2024 - Elsevier
Leakage in water distribution systems is a significant problem worldwide, leading to wastage
of water resources, compromised water quality and excess energy consumption. Leakage …

The technological emergence of automl: A survey of performant software and applications in the context of industry

A Scriven, DJ Kedziora, K Musial… - … and Trends® in …, 2023 - nowpublishers.com
With most technical fields, there exists a delay between fundamental academic research and
practical industrial uptake. Whilst some sciences have robust and well-established …

[HTML][HTML] Semi-supervised anomaly detection methods for leakage identification in water distribution networks: A comparative study

HM Tornyeviadzi, H Mohammed, R Seidu - Machine Learning with …, 2023 - Elsevier
This study presents a comprehensive evaluation of 10 state of the art semi-supervised
anomaly detection (AD) methods for leakage identification in water distribution networks …

Anomaly detection in quasi-periodic energy consumption data series: a comparison of algorithms

N Zangrando, P Fraternali, M Petri, NO Pinciroli Vago… - Energy …, 2022 - Springer
The diffusion of domotics solutions and of smart appliances and meters enables the
monitoring of energy consumption at a very fine level and the development of forecasting …

Random forest for the detection of unauthorized consumption in water supply systems: a case study in Southern Brazil

MR Stramari, A Kalbusch, E Henning - Urban Water Journal, 2023 - Taylor & Francis
Clandestine connections represent a significant portion of the apparent water losses. The
objective of this research work is to propose a systematic approach to inspect sites with …

Identifying major climate extreme indices driver of stream flow discharge variability using machine learning and SHaply Additive Explanation

Z Isa, AF Abdussalam, BA Sawa, M Ibrahim… - Sustainable Water …, 2023 - Springer
This study identifies major climate extreme indices as drivers of stream flow discharge
variability using machine learning and the SHaply Additive Explanation. The homogenized …

Comparison of automated machine learning (AutoML) libraries in time series forecasting Zaman serisi tahminlemede otomatikleştirilmiş makine öğrenmesi (AutoML) …

N Akkurt, S Hasgül - Journal of the Faculty of Engineering and …, 2024 - avesis.ogu.edu.tr
Companies must make forecasts for the future to take necessary precautions, as well as to
guard or expand their position and remain competitive. The development of data …

A review of leak detection and prediction methods in water distribution systems using machine learning

AS Acevedo Pérez - 2023 - repositorio.uniandes.edu.co
This paper presents a semi systematic literature review of recent research trends in the
detection and prediction of leaks and bursts in water dystribution systems using machine …

Addressing data limitations in leakage detection of water distribution systems

WYP Wu, S Liu, Z Kapelan - 2024 - repository.tudelft.nl
Leakage in water distribution systems is a significant problem worldwide, leading to wastage
of water resources, compromised water quality and excess energy consumption. Leakage …