A time-aware evaluation framework reveals that simple persistence forecasts outperform complex machine learning models while demonstrating that predictive accuracy and explanation quality diverge ...

A systematic review of 78 papers examines how machine learning methods support demand forecasting and inventory decision-making.

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 ...

A machine-learning correction layer built by a team led from MIT has roughly doubled the accuracy of the European Centre for Medium-Range Weather Forecasts model for forecasts two to six weeks ahead, ...

Successful test results of a new machine learning (ML) technique developed at Georgia Tech could help communities prepare for extreme weather and coastal flooding. The approach could also be applied ...

A team of researchers at the Universities of Lincoln, Sheffield, and Reading have developed a new method to improve the prediction of seasonal weather conditions in the U.K. and Northwest Europe. 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 ...

Australian scientists have identified conditions that could predict El Niño and La Niña events up to 12 months in advance.