Dual-branch Short-term Rainfall Forecasting Model Based on BiGRU-CapsNet and Transformer
LIU Rui
YE Chengxu
LIU Bing
Abstract：In recent years,various natural disasters caused by rainfall occur frequently,which have a great impact on People's daily life.Timely and accurate short-term rainfall prediction can remind people to take preventive measures.However,the weather factors affecting short-term rainfall are many and change quickly,so it is difficult to accurately predict short-term rainfall.In this paper,a dual-branch short-term rainfall prediction model based on BiGRU-CapsNet and Transformer is proposed.The prepro-cessed data are respectively input into BiGRU-CapsNet and Transformer for feature extraction,and then the extracted features are fused into the fully connected layer for short-term rainfall prediction.The experimental results show that the proposed model achieves good results in the evaluation indexes such as accuracy,precision and F1 score,and can accurately predict short-term rainfall.
Keywords：deep learningBiGRUCapsule NetworkTransformershort-term rainfall forecast
Publication Date：2025-07-20
Online Publishing Date：2025-09-25(First online date of this platform, not the publication date of the document)
Pages：6( 1862-1867 )