Application of the ARIMA-LSTM model in temperature prediction

Renxing Chen; Zuyi Huang; Zixun Zhou

doi:10.1117/12.2685944

28 July 2023 Application of the ARIMA-LSTM model in temperature prediction

Renxing Chen, Zuyi Huang, Zixun Zhou

Proceedings Volume 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023); 127563V (2023) https://doi.org/10.1117/12.2685944
Event: 2023 3rd International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2023), 2023, Tangshan, China

Abstract

This paper explores the application of ARIMA(AutoRegressive Integrated Moving Average) and LSTM(Long Short- Term Memory) in predicting future global temperatures in the context of climate change. The authors employ both ARIMA and LSTM models to describe past temperature trends and forecast future temperatures. Moreover, they combine the two models and consider residual analysis to establish an ARIMA-LSTM model with enhanced predictive performance. Results indicate that this model effectively predicts future global temperature changes.

Citation Download Citation

Renxing Chen, Zuyi Huang, and Zixun Zhou "Application of the ARIMA-LSTM model in temperature prediction", Proc. SPIE 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023), 127563V (28 July 2023); https://doi.org/10.1117/12.2685944

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