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A deep mixture density network for outlier-corrected interpolation of crowd-sourced weather data
[article]
2022
arXiv
pre-print
As the costs of sensors and associated IT infrastructure decreases - as exemplified by the Internet of Things - increasing volumes of observational data are becoming available for use by environmental scientists. However, as the number of available observation sites increases, so too does the opportunity for data quality issues to emerge, particularly given that many of these sensors do not have the benefit of official maintenance teams. To realise the value of crowd sourced 'Internet of
arXiv:2201.10544v1
fatcat:sxxq7ph3zbaddmt7j2dxtkxldm