BIOENGINEER

New AI Network Tackles Missing Data in Spatio-Temporal Forecasting

Researchers in Hangzhou have developed MGCRN, a graph-based recurrent neural network that maintains high forecasting accuracy ...
Nature

Water Level Forecasting Using Machine Learning Techniques articles from across Nature Portfolio

Uncover the latest and most impactful research in Water Level Forecasting Using Machine Learning Techniques. Explore pioneering discoveries, insightful ideas and new methods from leading researchers ...
Nature

Time Series Forecasting Techniques in Supply Chain Management

Time series forecasting is central to modern supply chain management, enabling organisations to anticipate future demand, optimise inventory levels and streamline logistics. Classical statistical ...
pv magazine International

New machine learning tech for short-term PV power generation forecasting

Researchers in China have applied a machine learning technology based on temporal convolutional networks in PV power forecasting for the first time. The new model reportedly outperforms similar models ...
Ars Technica

AI outperforms conventional weather forecasting for the first time: Google study

On Tuesday, the peer-reviewed journal Science published a study that shows how an AI meteorology model from Google DeepMind called GraphCast has significantly outperformed conventional weather ...
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 ...
techtarget

Predictive analytics vs. machine learning

Predictive analytics and machine learning help companies make better decisions by anticipating what will happen. Both approaches can predict future outcomes by analyzing current and past data. As such ...