Numerical and Machine Learning Methods to Predict the Thermal Behaviour of New Photovoltaic Cells in Order to Increase Their Efficiency
Crossref DOI link: https://doi.org/10.1007/s10765-026-03744-4
Published Online: 2026-03-21
Published Print: 2026-04
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Rehman, Ateeq Ur
Corasaniti, Sandra
Petracci, Ivano
Coppa, Paolo
Atzori, Dario
Text and Data Mining valid from 2026-03-21
Version of Record valid from 2026-03-21
Article History
Received: 22 January 2026
Accepted: 10 March 2026
First Online: 21 March 2026
Declarations
:
: The authors declare no competing interests.