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Statistics and pattern recognition applied to the spatio-temporal properties of seismicity /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Statistics and pattern recognition applied to the spatio-temporal properties of seismicity /editors, Stefania Gentili ... [et al.].
other author:	Gentili, Stefania,
Published:	Basel :MDPI,c2022.
Description:	vii, 170 p. :ill. (chiefly col.), col. maps ;25 cm.
Notes:	"This is a reprint of articles from the Special Issue published online in the open access journal Applied Sciences (ISSN 2076-3417)" -- t.p. verso.
Subject:	SeismologyData processing.
ISBN:	9783036542638 :

Statistics and pattern recognition applied to the spatio-temporal properties of seismicity /
Statistics and pattern recognition applied to the spatio-temporal properties of seismicity /editors, Stefania Gentili ... [et al.]. - Basel :MDPI,c2022. - vii, 170 p. :ill. (chiefly col.), col. maps ;25 cm.

"This is a reprint of articles from the Special Issue published online in the open access journal Applied Sciences (ISSN 2076-3417)" -- t.p. verso.

Includes bibliographical references.

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.

ISBN: 9783036542638 :NT$2298Subjects--Topical Terms:

485145
Seismology
--Data processing.

LC Class. No.: QE539

Dewey Class. No.: 551.22

Statistics and pattern recognition applied to the spatio-temporal properties of seismicity /
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245 0 0 $a Statistics and pattern recognition applied to the spatio-temporal properties of seismicity / $c editors, Stefania Gentili ... [et al.].
260 $a Basel : $b MDPI, $c c2022.
300 $a vii, 170 p. : $b ill. (chiefly col.), col. maps ; $c 25 cm.
500 $a "This is a reprint of articles from the Special Issue published online in the open access journal Applied Sciences (ISSN 2076-3417)" -- t.p. verso.
504 $a Includes bibliographical references.
520 $a 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.
650 0 $a Seismology $x Data processing. $3 485145
650 0 $a Big data. $3 609582
700 1 $a Gentili, Stefania, $e editor. $3 989901
700 1 $a Giovambattista, Rita Di, $e editor. $3 989902
700 1 $a Shcherbakov, Robert, $e editor. $3 989903
700 1 $a Vallianatos, Filippos, $e editor. $3 989904