A Comparative Study of Deep Learning Algorithms and SARIMA Models for Forecasting Monthly Solar Radiation and UV Index: Case Study for Mauritius
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-36246-0_26
Reference13 articles.
1. Huang, G.Y., Lai, C.J., Pai, P.F.: Forecasting hourly intermittent rainfall by deep belief networks with simple exponential smoothing. Water Resour. Manage. 36(13), 5207–5223 (2022)
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3. Doorga, J., Rughooputh, S., Boojhawon, R.: Geospatial Modelling of Solar Radiation Climate. In Geospatial Optimization of Solar Energy: Cases from Around the World, pp. 19–33. Springer International Publishing, Cham (2022)
4. Doorga, J.R., Rughooputh, S.D., Boojhawon, R.: Modelling the global solar radiation climate of Mauritius using regression techniques. Renew. Energy 131, 861–878 (2019)
5. Fioletov, V., Kerr, J.B., Fergusson, A.: The UV index: definition, distribution and factors affecting it. Can. J. Publ. Health 101, I5–I9 (2010)
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