Time-series prediction of hourly atmospheric pressure using ANFIS and LSTM approaches
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-022-07275-5.pdf
Reference42 articles.
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2. Tektaş M (2010) Weather forecasting using ANFIS and ARIMA models. Environ Res Eng Manag 51(1):5–10
3. Gaspar P, Ponte RM (1997) Relation between sea level and barometric pressure determined from altimeter data and model simulations. J Geophys Res Oceans 102(C1):961–971. https://doi.org/10.1029/96JC02920
4. Hossain M, Rekabdar B, Louis SJ, S Dascalu (2015) Forecasting the weather of Nevada: a deep learning approach. In 2015 international joint conference on neural networks (IJCNN) IEEE, pp 1–6. https://doi.org/10.1109/ijcnn.2015.7280812
5. La Rocca P, Riggi D, Riggi F (2010) Time series analysis of barometric pressure data. Eur J Phys 31(3):645. https://doi.org/10.1088/0143-0807/31/3/022
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