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

The innovation at the heart of this research lies in combining Long Short-Term Memory (LSTM) networks and Recurrent Neural Networks (RNNs) to tackle financial time series data. These architectures ...

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory, attention ...