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 …

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 …

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 …

The energy demand and their associated costs in pressurized irrigation networks together
with water scarcity are currently causing serious challenges for irrigation district's (ID) …

In a world where the availability of water is decreasing, its use must be thoroughly optimized.
Irrigated agricultural systems, as the main user of the planet's fresh water, must improve its …

The balance between water supply and demand requires efficient water supply system
management techniques. This balance is achieved through operational actions, many of …

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 …

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 …

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

Rice is one of the world's most popular food crops. Since its production is dependent on
intensive water use, water management is critical to ensure sustainability of water resource …