Classification of the Ionospheric Disturbances Caused by Geomagnetic and Seismic Activity with K-Nearest Neighbors Algorithm

Detection of earthquake-precursor signals a few days before the earthquake day has become an area of increasing interest. In recent years, it has been observed that the major earthquakes and geomagnetic activity can cause significant disturbances and anomalies in the ionospheric parameters such as Total Electron Content (TEC). TEC provides important information about the detection of anomalies and disturbances related to seismic and geomagnetic activity in the ionosphere. The main goal of this study is to classify the disturbances due to the seismic and geomagnetic activity in the ionosphere using TEC data. For this purpose, the K-Nearest Neighbors (K-NN) algorithm is applied to TEC estimated from Global Positioning System stations during five earthquakes with magnitudes Mw greater than 5.6 between 1999 and 2016 and for the geomagnetically quiet and disturbed conditions of the ionosphere. The data is divided into four classes as non-earthquake and non-geomagnetic activity, geomagnetic activity, possible earthquake precursor and earthquake for each earthquake. The study is performed into two groups as Group I, where five days before the earthquake day are marked as precursor, and Group II, where three days are marked as precursors. It is observed that 5055 test samples out of a total of 5184 are classified as true whereas 129 are classified as false for Group I. 3912 are classified as true and 105 are classified as false for Group II. For the possible earthquake class, the Accuracy values increase inversely with the distance of the stations from the epicenter and directly related to the magnitude of the earthquakes.