极地研究2025，Vol.37Issue(3)：427-436,10.DOI:10.13679/j.jdyj.20240016
基于Swin Transformer的太空台风识别模型
A Swin Transformer-based space hurricane identification model
摘要
Abstract
A space hurricane is a vortex-like auroral bright-spot structure that occurs in the polar cap region during quiet geomagnetic periods and is caused by the local injection of a large amount of solar wind energy into the polar ionosphere,comparable to a magnetic storm.Achieving accurate and effective identification of space hurricane events from a large amount of auroral data is essential for studies of solar wind energy in-jection.In this paper,a Swin Transformer model,which is used to identify space hurricanes from Defense Meteorological Satellite Program/Special Sensor Uleraviolet Spectrographic Imager(DMSP/SSUSI)images,is constructed.This model improves computation time using splitting windows and establishes inter-window information transfer channels using the Shifted Window Multi-Head Self-Attention(SW-MSA)method,achieving automatic identification of space hurricanes.The study demonstrates that the model trained using a dataset consisting of space hurricanes in the northern and southern hemispheres identifies space hurricane events more accurately.The accuracy of the Swin Transformer-based space hurricane identification model is 95.94%.关键词
Swin Transformer/太空台风/识别模型/深度学习Key words
Swin Transformer/space hurricane/identification model/deep learning引用本文复制引用
乔枫,张清和,邢赞扬,王勇,马羽璋,陆盛,张红波,王飞飞..基于Swin Transformer的太空台风识别模型[J].极地研究,2025,37(3):427-436,10.基金项目
国家自然科学基金(42325404,42120104003,42441828,42474219)、山东省自然科学基金(ZR2022MD034,ZR2022QD077)、小米青年学者项目和北极黄河地球系统国家野外科学观测研究站开放研究基金(YRNORS-20242606)资助 （42325404,42120104003,42441828,42474219）
