Time-Series Analysis of Meteorological Data Using AI Techniques

Deepak Kumar Sharma ,Shubhra Dixit

Time-Series Analysis of Meteorological Data Using AI Techniques

Authors

Deepak Kumar Sharma ,Shubhra Dixit

Keywords:

Time-Series Analysis, Meteorological Data, Transformer, Bidirectional LSTM, GRU, Seasonality Decomposition

Abstract

Meteorological data is one of the richest sources of time-series information available today.Every hour, thousands of weather stations, satellites, and sensors record changes in temperature, pressure, humidity, and other variables, creating long sequences that hold patternsabout climate behavior. Making sense of these sequences is not easy because

References

Box, G.E.P., Jenkins, G.M., Reinsel, G.C. and Ljung, G.M. (2015) Time Series Analysis: Forecasting and Control. 5th edn. Hoboken: Wiley.

Lim, B. and Zohren, S. (2021) 'Time-series forecasting with deep learning: A survey', Philosophical Transactions of the Royal Society A, 379(2194), pp. 1–14.

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Published

2024-12-20

How to Cite

Deepak Kumar Sharma ,Shubhra Dixit. (2024). Time-Series Analysis of Meteorological Data Using AI Techniques. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 8861–8871. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5524