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Application of explainable machine learning for estimating direct and diffuse components of solar ir...

Application of explainable machine learning for estimating direct and diffuse components of solar ir...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_8a067097fdba4847aa4685d991f16b3b

Application of explainable machine learning for estimating direct and diffuse components of solar irradiance

About this item

Full title

Application of explainable machine learning for estimating direct and diffuse components of solar irradiance

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2025-03, Vol.15 (1), p.7402-18, Article 7402

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

The inclusion of diffuse horizontal irradiance (DHI) and direct normal irradiance (DNI) is crucial in the context of solar energy applications. However, most solar irradiance instruments primarily prioritize the measurement of global horizontal irradiance (GHI) due to the high cost associated with devices used to measure DNI and DHI. Hence, numerou...

Alternative Titles

Full title

Application of explainable machine learning for estimating direct and diffuse components of solar irradiance

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_8a067097fdba4847aa4685d991f16b3b

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_8a067097fdba4847aa4685d991f16b3b

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-025-91158-x

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