Geomagnetic data prediction with deep learning under the constraint of reference channel data
Compared to existing time‐series methods, this approach substantially enhances reliability and robustness against varying noise intensities and types; compared to the magnetotelluric remote reference method, it drastically lowers reference data requirements, yielding significantly greater flexibility.