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 ...

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.

Picture a single forecasting mistake triggering a cascade of negative consequences, such as surplus inventory, strained supplier relationships and disappointed customers. In today's world, accurate ...

AI market forecasting uses predictive analytics and strategic planning tools to anticipate demand shifts, optimize decisions, ...

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 ...

Every day, meteorologist Hannah Wangari takes the free graphs and maps produced by the five forecasting models she subscribes to and interprets what she sees. “What’s the likelihood of rain in ...

Cosmic rays are high-energy particles that constantly bombard Earth from space and are influenced by the sun's magnetic activity. When the sun is active, fewer of these particles reach Earth; when the ...

Joshua S. Fu received funding from U. S. EPA for wildfire and human health studies. Wildfire smoke from Canada’s extreme fire season has left a lot of people thinking about air quality and wondering ...

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 ...