Insights into the prediction of the liquid density of refrigerant systems by artificial intelligent approaches
Crossref DOI link: https://doi.org/10.1038/s41598-024-53007-1
Published Online: 2024-01-29
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Li, Huaguang
Baghban, Alireza
Text and Data Mining valid from 2024-01-29
Version of Record valid from 2024-01-29
Article History
Received: 4 November 2023
Accepted: 25 January 2024
First Online: 29 January 2024
Competing interests
: The authors declare no competing interests.