A recent study has introduced a new machine learning model aimed at improving the accuracy of renewable energy forecasting. Published in March 2021 under the title An Efficient Supervised Machine ...

Ph.D. student Phillip Si and Assistant Professor Peng Chen developed Latent-EnSF, a technique that improves how ML models assimilate data to make predictions.

One of the unwritten axioms of data scientists specializing in machine learning methodologies is that they all try their hand at predicting the stock market. Some of the best attempts have turned a ...

A range of national meteorological services across Europe and ECMWF have launched Anemoi, a framework for creating machine learning (ML) weather forecasting systems. Named after the Greek gods of the ...

In this paper we investigate oil market volatility prediction using a comprehensive data set of 205 variables spanning macroeconomic, financial, energy-related and sentiment indicators. We employ ...

The Writer As climate extremes intensify across Africa, the need for accurate and timely weather prediction has become increasingly urgent.Floods, heatwaves, droughts, and air pollution events are ...