Prediction of daily global solar radiation and air temperature using six machine learning algorithms; a case of 27 European countries

Nematchoua Kameni, Modeste; Kameni Nematchoua, Modeste

doi:10.1016/j.ecoinf.2022.101643

Article (Scientific journals)

Prediction of daily global solar radiation and air temperature using six machine learning algorithms; a case of 27 European countries

Nematchoua Kameni, Modeste; Kameni Nematchoua, Modeste

2022 • In Ecological Informatics

Peer Reviewed verified by ORBi

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https://hdl.handle.net/2268/289680

DOI
10.1016/j.ecoinf.2022.101643

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Keywords :

Solar radiation Europe, machine-learning Prediction

Disciplines :

Architecture
Civil engineering
Energy

Author, co-author :

Nematchoua Kameni, Modeste

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

Language :

English

Title :

Prediction of daily global solar radiation and air temperature using six machine learning algorithms; a case of 27 European countries

Publication date :

15 April 2022

Journal title :

Ecological Informatics

ISSN :

1574-9541

eISSN :

1878-0512

Publisher :

Elsevier, Amsterdam, Netherlands

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 16 April 2022

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