In today's fast-paced global economy coupled with the availability of mobile internet and
social networks, several business models have been disrupted. This disruption brings a …

The challenge for city authorities goes beyond managing growing cities, since as cities
develop, their exposure to climate change effects also increases. In this scenario, urban …

This paper presents a completely data-driven and machine-learning-based approach, in two
stages, to first characterize and then forecast hourly water demand in the short term with …

Smart meters installed at the user-level provide a new data source for managing water
infrastructure. This research explores the use of machine learning methods, including …

An accurate prediction of future water consumption is necessary to create a satisfactory
design for a water distribution system. In this study, two new hybrid approaches are …

Digital or intelligent water meters are being rolled out globally as a crucial component in
improving urban water management. This is because of their ability to frequently send water …

This study intensively examined the monthly water consumption forecasting performance
using advanced time series (ARIMA) models. Thus, this study intends to identify the …

Bayesian optimization has become a widely used tool in the optimization and machine
learning communities. It is suitable to problems as simulation/optimization and/or with an …

Modern solutions in water distribution systems are based on monitoring the quality and
quantity of drinking water. Identifying the volume of water consumption is the main element …

Water supply systems are essential for a modern society. This article presents an overview
of the latest research related to information and communication technology systems for …