This work shows the application of machine learning (ML) methods to the modeling of water
demand for the first time. Classification and regression trees (CART) and random forest (RF) …

One of the goals of efficient water supply management is the regular supply of clean water at
the pressure required by consumers. In this context, predicting water consumption in urban …

Technology has been increasingly applied in search for excellence in water resource
management. Tools such as demand-forecasting models provide information for utility …

The application of artificial neural network (ANN) models for short-term (15 min) urban water
demand predictions is evaluated. Optimization of the ANN model's hyperparameters with a …

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 …

Peak daily water demand forecasts are required for the cost-effective and sustainable
management and expansion of urban water supply infrastructure. This paper compares …

Efficient operation of urban water systems necessitates accurate water demand forecasting.
We present daily, weekly, and monthly water demand forecasting using dynamic artificial …

Reservoir planning and management are critical to the development of the hydrological field
and necessary to Integrated Water Resources Management. The growth of forecasting …

This article proposes a new general approach in short-term water demand forecasting
based on a two-stage learning process that couples time-series clustering with gene …

Storage dams play a very important role in irrigation especially during lean periods. For
proper regulation one should make sure the availability of water according to needs and …