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[null,"1.","Record Nr.",null,"UNINA9910674369603321"]
[null,null,"Autore",null,"Gentili Stefania"]
[null,null,"Titolo",null,"Statistics and Pattern Recognition Applied to the Spatio-Temporal Properties of Seismicity"]
[null,null,"Pubbl/distr/stampa",null,"Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022"]
[null,null,"Descrizione fisica",null,"1 online resource (180 p.)"]
[null,null,"Soggetti",null,"Environmental science, engineering and technology"]
[{"$nulls":4},"Technology: general issues"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","Due to the significant increase in the availability of new data in recent years, as a result of the expansion of available seismic stations, laboratory experiments, and the availability of increasingly reliable synthetic catalogs, considerable progress has been made in understanding the spatiotemporal properties of earthquakes. The study of the preparatory phase of earthquakes and the analysis of past seismicity has led to the formulation of seismicity models for the forecasting of future earthquakes or to the development of seismic hazard maps. The results are tested and validated by increasingly accurate statistical methods. A relevant part of the development of many models is the correct identification of seismicity clusters and scaling laws of background seismicity. In this collection, we present eight innovative papers that address all the above topics. The occurrence of strong earthquakes (mainshocks) is analyzed from different perspectives in this Special Issue."]