Machine learning models to complete rainfall time series databases affected by missing or anomalous data
Crossref DOI link: https://doi.org/10.1007/s12145-023-01122-4
Published Online: 2023-10-20
Published Print: 2023-12
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Lupi, Andrea
Luppichini, Marco
Barsanti, Michele
Bini, Monica
Giannecchini, Roberto
Text and Data Mining valid from 2023-10-20
Version of Record valid from 2023-10-20
Article History
Received: 7 July 2023
Accepted: 7 October 2023
First Online: 20 October 2023
Declarations
:
: The authors declare no competing interests.