In a recent paper, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and co-author William Gilpin show that a deceptively ...

The peer-reviewed research, published in npj Climate and Atmospheric Science, assesses the viability of applying a machine learning (ML) weather model to global seasonal forecasts, which are vital for ...

Put down the pen and paper and shelve the spreadsheets. Artificial intelligence (AI) and advanced machine learning are the next-generation tools for demand forecasting in distribution. That was the ...

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 ...

Artificial intelligence-driven algorithms can be used to better forecast models for natural disasters, saving lives and protecting property by rapidly analyzing massive data sets and identifying ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Solar flares strong enough to knock out satellites and buckle power grids are, by definition, rare. That rarity is exactly ...

David J. Silvester, a mathematics professor at the University of Manchester, has developed a novel machine-learning method to ...