Hybrid models for direct normal irradiance forecasting: a case study of Ghardaia zone (Algeria)

Boumediene Ladjal (), Imad Eddine Tibermacine (), Mohcene Bechouat (), Moussa Sedraoui (), Christian Napoli (), Abdelaziz Rabehi () and Djemoui Lalmi ()
Additional contact information
Boumediene Ladjal: Université de Ghardaia
Imad Eddine Tibermacine: Sapienza University of Rome
Mohcene Bechouat: Université de Ghardaia
Moussa Sedraoui: University 8 Mai 1945 Guelma
Christian Napoli: Sapienza University of Rome
Abdelaziz Rabehi: University of Djelfa
Djemoui Lalmi: Université de Ghardaia

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 15, No 39, 14703-14725

Abstract: Abstract This study presents a resilient model for accurately predicting annual solar radiation in Ghardaia, Algeria, utilizing a locally-sourced database. The model integrates temperature, humidity, wind speed, and pressure as inputs. A combination of machine learning and deep learning techniques, including convolutional neural networks and conventional neural networks, are employed to forecast direct normal irradiance and diffuse solar radiation. This comprehensive approach uses multivariate regression analysis, validated with established databases for high-resolution analysis in data-scarce regions. The findings highlight the model’s effectiveness in providing precise forecasts and outline potential applications for optimizing solar energy use in similar climates.

Keywords: Multivariate regression analysis; Neural networks; Convolutional neural networks; Irradiance prediction (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11069-024-06837-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:120:y:2024:i:15:d:10.1007_s11069-024-06837-1

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-024-06837-1

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().