In recent years, a significant evolution of forecasting methods has been possible due to
advances in artificial computational intelligence. The achievement of the optimal architecture …

Highlights•Forecasting of daily irrigation water demand model with data available is
limited.•The Bayesian framework approach and GAs were used to find the optimal ANN.•The …

Recently, Computational Neural Networks (CNNs) and fuzzy inference systems have been
successfully applied to time series forecasting. In this study the performance of a hybrid …

Nowadays, water scarcity and the increase in energy demand and their associated costs in
pressurized irrigation systems are causing serious challenges. In addition, most of these …

Efficient management of a drinking water network reduces the economic costs related to
water production and transport (pumping). Model predictive control (MPC) is nowadays a …

Information regarding water demand is key to managing consumption in irrigation districts.
Forecasting water demand is one of the main problems for designers and managers of water …

The evolution of smart water grids leads to new Big Data challenges boosting the
development and application of Machine Learning techniques to support efficient and …

Water demand in Tehran city has risen remarkably in the past few decades due to the city's
increasing population and economic development. This has led to a need for better planning …

One of the main problems in the management of large water supply and distribution systems
is the forecasting of daily demand in order to schedule pumping effort and minimize costs …

In this paper, a Multi-Objective Genetic Algorithm (MOGA) framework for the design of
Artificial Neural Network (ANN) models is used to design 1-step-ahead prediction models of …