A user-friendly and accurate machine learning tool for the evaluation of the worldwide yearly photovoltaic electricity production

Domenico Mazzeo*, Sonia Leva, Nicoletta Matera, Karolos J. Kontoleon, Shaik Saboor, Behrouz Pirouz, Mohamed R. Elkadeem

*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Fingerprint

Dive into the research topics of 'A user-friendly and accurate machine learning tool for the evaluation of the worldwide yearly photovoltaic electricity production'. Together they form a unique fingerprint.

Engineering

Material Science

Chemical Engineering