Caitst: conv-attentional image time sequence transformer for ionospheric tec maps forecast

HIGHLIGHTS

  • who: Guozhen Xia and collaborators from the Department of Space Physics, School of Electronic Information, Wuhan University, Wuhan, China have published the Article: CAiTST: Conv-Attentional Image Time Sequence Transformer for Ionospheric TEC Maps Forecast, in the Journal: (JOURNAL) of 20/Dec/2021
  • what: The authors propose the (CAiTST) a transformer-based sequences prediction model equipped with convolutional networks and an mechanism. The authors compare the results of with those of the 1-day Center for Orbit Determination in Europe (CODE) prediction model. The study shows that the model and its unique attention mechanism are . . .

     

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