In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

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.

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 ...

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 ...

Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting ...

The recent advent of AI is transforming daily life from streamlining routine tasks to augmenting productivity and facilitating data-driven decisions.

Enterprises that continue to layer AI onto existing analytics frameworks will continue to see incremental gains. Those that ...

The ITU Journal on Future and Evolving Technologies continues its in-depth coverage of machine learning for 5G and future networks.

Digital twins and prognostic models deliver detailed insights into a battery’s behaviour and lifespan, and machine learning..