Evidence, limitations and implications for renewable energy planning of daily global solar irradiation in tropical climate zones of Cameroon, predicted by machine learning

Ndackssi, Wilson Nathan; Kameni Nematchoua, Modeste

doi:10.1007/s43621-026-04807-0

Article (Scientific journals)

Evidence, limitations and implications for renewable energy planning of daily global solar irradiation in tropical climate zones of Cameroon, predicted by machine learning

Ndackssi, Wilson Nathan; Kameni Nematchoua, Modeste

2026 • In Discover sustainability

Peer Reviewed verified by ORBi

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https://hdl.handle.net/2268/349518

DOI
10.1007/s43621-026-04807-0

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Disciplines :

Computer science

Author, co-author :

Ndackssi, Wilson Nathan

Kameni Nematchoua, Modeste ; Université de Liège - ULiège > Urban and Environmental Engineering

Language :

English

Title :

Evidence, limitations and implications for renewable energy planning of daily global solar irradiation in tropical climate zones of Cameroon, predicted by machine learning

Publication date :

27 September 2026

Journal title :

Discover sustainability

eISSN :

2662-9984

Publisher :

Springer Science and Business Media LLC

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://link.springer.com/article/10.1007/s43621-026-04807-0

Available on ORBi :

since 08 October 2026

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