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.

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 ...

This study was led by Professor Qi Zhong and Professor Xiuping Yao from the China Meteorological Administration Training Center, and Assistant Engineer Zhicha Zhang from the Zhejiang Meteorological ...

A new system for forecasting weather and predicting future climate uses artificial intelligence (AI) to achieve results comparable with the best existing models while using much less computer power, ...

Construction projects generate constant signals about cost, schedule, labor, safety and risk, but predictive analytics turns ...

A Systematic Review of Adoption, Barriers and Strategic Implications and published in Administrative Sciences, reviewed 37 peer-reviewed studies from 2015 to 2025 and found that AI-driven demand ...

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 ...

As the world grapples with the energy crisis and environmental concerns, the focus on renewable energy sources has intensified. Lithium-ion batteries, with their high energy density and low pollution, ...