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 ...

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...

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 ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

Discover how predictive analytics uses data-driven models like decision trees and neural networks to forecast outcomes and ...

A University of Manchester researcher has developed a machine-learning method to spot sudden changes in fluid behavior, known as bifurcation points, before traditional simulations fail. The approach ...

Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of organic materials ...

A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...

Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...