Predicting Meteorological Variables on Local Level with SARIMA, LSTM and Hybrid Techniques

Predicting Meteorological Variables on Local Level with SARIMA, LSTM and Hybrid Techniques

The choice of holiday destinations is highly depended on climate considerations. Nowadays, since the effects of the climate crisis are being increasingly felt, the need for accurate weather and climate services for hotels is crucial. Such a service could be beneficial for both the future planning of...

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Bibliographic Details
Main Authors: Antonios Parasyris, George Alexandrakis, Georgios V. Kozyrakis, Katerina Spanoudaki, Nikolaos A. Kampanis
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Atmosphere
Subjects:
SARIMA
artificial neural networks (ANN)
LSTM
hybrid methodologies
prediction
in situ measurements
Online Access:https://www.mdpi.com/2073-4433/13/6/878

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