Application of machine learning methods to study the relationships between seismicity and geodynamic features of the Dnister Hydropower Complex

• Datum: 2026
• Hauptverfasser: Brusak, Ivan, Haidus, Oleg, Kuplovskyi, Bohdan
• Format: Artikel
• Sprache: Englisch
• Veröffentlicht: S. Subbotin Institute of Geophysics of the NAS of Ukraine 2026
• Schlagworte: Seismicity; recent geodynamics; reservoir-triggered seismicity; water level changes; Dnister Hydro Power Complex; machine learning
• Online Zugang: https://journals.uran.ua/geofizicheskiy/article/view/350985
• Назва журналу: Geofizicheskiy Zhurnal

This study investigates the seismicity and recent geodynamic features of the Dnister Hydropower Complex in Ukraine, emphasizing the application of machine learning methods to analyze their interrelationships. The complex, situated in a seismically active transitional zone, is influenced by natural t...