Short-time water demand forecasting is essential for optimal control in a water distribution
system (WDS). Current methods (eg, time-series models and conventional artificial neural …

Short-term water demand forecasting (StWDF) is the foundation stone in the derivation of an
optimal plan for controlling water supply systems. Deep learning (DL) approaches provide …

Water is an important resource for life and its existence. Water demand is increasing with
increasing economic growth and population, while the water availability is continually …

Short-term water demand forecast is one of the most important technology for urban water
supply management. The accuracy and timeliness of the forecast have an important impact …

Demand forecasting plays a vital role in resource management for governments and private
companies. Considering the scarcity of water and its inherent constraints, demand …

Regression Tree (RT) forecasting models are widely used in short-term demand forecasting.
Likewise, Self-Organizing Maps (SOM) models are known for their ability to cluster and …

Short-term water demand forecasting models address the case of a real-time optimal water
pumping schedule. This study focuses on developing artificial neural network (ANN) models …

A reliable and accurate urban water demand forecasting plays a significant role in building
intelligent water supplying system and smart city. Due to the high frequency noise and …

This paper addressed the problem of water-demand forecasting for real-time operation of
water supply systems. The present study was conducted to identify the best fit model using …

Predicting urban water demand is important in rationalizing water allocation and building
smart cities. Influenced by multifarious factors, water demand is with high-frequency noise …