Explainable Artificial Intelligence (XAI) Model for Earthquake Spatial Probability Assessment in Arabian Peninsula

Among all the natural hazards, earthquake prediction is an arduous task. Although many studies have been published on earthquake hazard assessment (EHA), very few have been published on the use of artificial intelligence (AI) in spatial probability assessment (SPA). There is a great deal of complexi...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Remote sensing (Basel, Switzerland) Jg. 15; H. 9; S. 2248
Hauptverfasser:	Jena, Ratiranjan, Shanableh, Abdallah, Al-Ruzouq, Rami, Pradhan, Biswajeet, Gibril, Mohamed Barakat A., Khalil, Mohamad Ali, Ghorbanzadeh, Omid, Ganapathy, Ganapathy Pattukandan, Ghamisi, Pedram
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 24.04.2023
Schlagworte:	Accuracy Algorithms Arabian peninsula Artificial intelligence Comparative analysis Deep learning Digital Elevation Models Digital imaging Earthquake prediction earthquake spatial probability assessment Earthquakes Explainable artificial intelligence Fault lines Geological hazards Geological surveys geophysics GIS Hazard assessment hazard characterization hybrids inception v3-XGBoost inventories Landsat Landsat satellites Machine learning Model accuracy Modelling Neural networks prediction Prediction models Probability probability analysis Remote sensing Satellite imagery Seismic activity Seismic hazard Seismology Shaking Tectonics Turkey (country) United States Geological Survey XAI United Arab Emirates Saudi Arabia Arabian Peninsula Iran Gulf of Aden Red Sea Gulf of Aqaba Indonesia Dead Sea
ISSN:	2072-4292, 2072-4292
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!