Recent advancements in neural network methodologies have revolutionised hydrological forecasting, enabling more accurate, robust and computationally efficient predictions of water resource dynamics.

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...

Economic policymaking relies upon accurate forecasts of economic conditions. Current methods for unconditional forecasting are dominated by inherently linear models that exhibit model dependence and ...

In the AI era, pure data-driven meteorological and climate models are gradually catching up with, and even surpassing, traditional numerical models. However, significant challenges persist in current ...

Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...

With legacy load forecasting models struggling with unpredictable events that are becoming ever more common, power-hungry AI ...

As the world grapples with the energy crisis and environmental concerns, the focus on renewable energy sources has intensified. Lithium-ion batteries, with their high energy density and low pollution, ...

Bernard Benson, Edward Brown, Stefano Bonasera, Giacomo Acciarini, Jorge A. Pérez-Hernández, Eric Sutton, Moriba K. Jah, Christopher Bridges, Meng Jin, Atılım Güneş Baydin Solar radio flux along with ...