forecasting
This data repository comprises three distinct datasets tailored for different predictive modeling tasks. The first dataset is a synthetic dataset designed to simulate multivariate time series patterns, incorporating both linear and non-linear dependencies among input and target features. The second dataset, the Beijing Air Quality PM2.5 dataset, consists of PM2.5 measurements alongside meteorological data like temperature, humidity, and wind speed, with the objective of predicting PM2.5 concentrations.
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The unfolding of the COVID-19 outbreak was an unprecedented and unanticipated opportunity to understand how a sudden global shock modulates people’s online searches when seeking information about their emotional well-being. Furthermore, it also illustrated how public health surveillance systems were essential for tracking diseases’ spatial and temporal dynamics and shaping rapid public policy changes.
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