A hybrid XGBoost-ISSA-LSTM model for accurate short-term and long-term dissolved oxygen prediction in ponds
Crossref DOI link: https://doi.org/10.1007/s11356-021-17020-5
Published Online: 2021-10-22
Published Print: 2022-03
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Wu, Yuhan
Sun, Longqing https://orcid.org/0000-0002-7387-3334
Sun, Xibei
Wang, Boning
Text and Data Mining valid from 2021-10-22
Version of Record valid from 2021-10-22
Article History
Received: 19 July 2021
Accepted: 9 October 2021
First Online: 22 October 2021
Declarations
:
: Not applicable.
: The authors declare no competing interests.