earticle

영어

The ionosphere is the part of the Earth's atmosphere with a high concentration of free electrons and ions. The ionosphere is characterised by its variability and inhomogeneity. One of the characteristic inhomogeneities is the so-called auroral oval, which determines the range of auroral radiance. Detection of the auroral oval is an important task for forecasting auroral storms, as they affect long-range communication systems, navigation, satellite-to-ground communications, making communications complicated or impossible. Therefore, an auroral oval detection and prediction needs to be performed in order to be informed about the area of their possible influence at certain time intervals. On the basis of the available image dataset from SIMuRG, which is based on GNSS data, it is proposed to use the LSTM model and CNN architecture. The paper reviews existing implementations and proposes a method for predicting auroral oval movements in the images, using the Convolutional LSTM architecture, which combines time series processing and computer vision. The work results in a machine learning model that can make the predictions based on even small sets of data.