Classification of the Ionospheric Disturbances Caused by Geomagnetic and Seismic Activity with K-Nearest Neighbors Algorithm
Yazarlar (4)
Doç. Dr. Cafer Budak Dicle Üniversitesi, Türkiye
Doç. Dr. Seçil KARATAY Kastamonu Üniversitesi, Türkiye
Dr. Öğr. Üyesi Faruk ERKEN Kastamonu Üniversitesi, Türkiye
Arş. Gör. Ali ÇINAR Kastamonu Üniversitesi, Türkiye
Makale Türü Açık Erişim Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
Dergi Adı Wireless Personal Communications (Q3)
Dergi ISSN 0929-6212 Dergi Bilgileri (2024)
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili Türkçe Basım Tarihi 04-2024
Kabul Tarihi 10-03-2024 Yayınlanma Tarihi 01-02-2024
Cilt / Sayı / Sayfa 134 / 3 / 1551–1569 DOI 10.1007/s11277-024-10965-z
Makale Linki http://dx.doi.org/10.1007/s11277-024-10965-z
UAK Araştırma Alanları
Elektrik-Elektronik Mühendisliği
Özet
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 …
Anahtar Kelimeler
Classification | Disturbance | Earthquake | Ionosphere | K-nearest neighbors
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Web of Science 10
Scopus 12
Google Scholar 15
Classification of the Ionospheric Disturbances Caused by Geomagnetic and Seismic Activity with K-Nearest Neighbors Algorithm

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