RAINFALL PREDICTION FOR QINGMING FESTIVAL BASED ON ARIMA-LSTM MODEL

Requent rainfall during the Qingming Festival period has impacted public travel, cultural and tourism activities, as well as urban management. Based on nearly 20 years of meteorological data, this study develops an ARIMA-LSTM hybrid model to model and predict rainfall patterns in five representative cities: Xi’an, Turpan, Wuyuan, Hangzhou, and Wuhan. The results indicate that the model demonstrates strong fitting accuracy and stability, with an average R2 of 0.84196 and a prediction accuracy of 89.9%. After incorporating a real-time correction mechanism, the model’s responsiveness to abrupt weather changes improved, with error control enhanced by over 15%. This study provides data support and methodological reference for short-term meteorological services and public travel during the Qingming Festival.

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Publication Details

Journal
Frontiers in Environmental Research
Published
2025-08-28
DOI
https://doi.org/10.61784/fer3034
Primary Topic
Advanced Technologies in Various Fields
Type
article
Field-Weighted Citation Impact
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article

RAINFALL PREDICTION FOR QINGMING FESTIVAL BASED ON ARIMA-LSTM MODEL

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Frontiers in Environmental Research
Advanced Technologies in Various Fields
article

RAINFALL PREDICTION FOR QINGMING FESTIVAL BASED ON ARIMA-LSTM MODEL

article en

Abstract

Requent rainfall during the Qingming Festival period has impacted public travel, cultural and tourism activities, as well as urban management. Based on nearly 20 years of meteorological data, this study develops an ARIMA-LSTM hybrid model to model and predict rainfall patterns in five representative cities: Xi’an, Turpan, Wuyuan, Hangzhou, and Wuhan. The results indicate that the model demonstrates strong fitting accuracy and stability, with an average R2 of 0.84196 and a prediction accuracy of 89.9%. After incorporating a real-time correction mechanism, the model’s responsiveness to abrupt weather changes improved, with error control enhanced by over 15%. This study provides data support and methodological reference for short-term meteorological services and public travel during the Qingming Festival.

Frontiers in Environmental ResearchVol. 3(3)
Xi'an Shiyou University (CN)
Climate action
Openalex Percentile: Top 88%
Advanced Technologies in Various Fields
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