Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...
Researchers in China conceived a new PV forecasting approach that integrates causal convolution, recurrent structures, attention mechanisms, and the Kolmogorov–Arnold Network (KAN). Experimental ...
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 ...
Predicting tropical cyclones (TCs) accurately is crucial for disaster mitigation and public safety. Although the forecasting accuracy of TC tracks has improved substantially in recent decades, ...
Spatiotemporal Evolution Patterns and Intelligent Forecasting of Passenger Flow in Megacity High-Speed Rail Hubs: A Case ...
Energy use in healthcare is a growing policy concern. Hospitals account for a significant share of public sector emissions, ...
In order to understand currents, tides and other ocean dynamics, scientists need to accurately capture sea surface height, or ...
Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...
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