Global horizontal and direct normal solar irradiance modeling by the machine learning methods XGBoost and deep neural networks with CNN-LSTM layers: a case study using the GOES-16 satellite imagery-Reference-Cited by-同舟云学术

Global horizontal and direct normal solar irradiance modeling by the machine learning methods XGBoost and deep neural networks with CNN-LSTM layers: a case study using the GOES-16 satellite imagery

Published:2022-04-19 Issue:4 Volume:13 Page:1271-1286
ISSN:2008-9163
Container-title:International Journal of Energy and Environmental Engineering
language:en
Short-container-title:Int J Energy Environ Eng

Author:

Rocha Paulo A. C.^ORCID,Santos Victor Oliveira

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Springer Science and Business Media LLC

Subject

General Energy,Environmental Engineering

Link

https://link.springer.com/content/pdf/10.1007/s40095-022-00493-6.pdf

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