Economist Barbara Rossi has outlined a new method of assessing large numbers of big data-driven forecast models. Rossi told a ...

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 ...

Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new ...

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 ...

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 ...

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 ...