Nature

Prediction of electricity consumption and hydropower production in the smart power grid based on the gated recurrent unit neural network and modified future search algorithm

In the current dynamic energy environment, the combination of renewable energy sources and the rise of intelligent power grids have highlighted the crucial need for precise and effective energy ...
Nature

An ODE based neural network approach for PM2.5 forecasting

Predicting time-series data is inherently complex, spurring the development of advanced neural network approaches. Monitoring and predicting PM2.5 levels is especially challenging due to the interplay ...
Booth School of Business

Paper Recurrent Neural Networks for Nonlinear Time Series

This study bridges classical time-series econometrics with modern machine learning by establishing theoretical performance guarantees for recurrent neural networks (RNNs) applied to complex ...
techtimes

Forecasting the Future: How AI Is Reshaping Financial Predictions

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 ...