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220822 ||| eng |
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|a 9783036542638
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|a 9783036542645
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|a books978-3-0365-4264-5
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|a Gentili, Stefania
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| 245 |
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0 |
|a Statistics and Pattern Recognition Applied to the Spatio-Temporal Properties of Seismicity
|h Elektronische Ressource
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| 260 |
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|a Basel
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2022
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| 300 |
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|a 1 electronic resource (180 p.)
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| 653 |
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|a machine learning
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| 653 |
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|a foreshocks and aftershocks
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| 653 |
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|a smoothed seismicity methods
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| 653 |
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|a earthquake simulator
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| 653 |
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|a earthquake forecasting model
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| 653 |
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|a California
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| 653 |
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|a earthquake likelihood models
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| 653 |
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|a markovian arrival processes
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| 653 |
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|a earthquake forecasting
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| 653 |
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|a tapered Gutenberg-Richter
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| 653 |
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|a n/a
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| 653 |
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|a statistical seismology
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| 653 |
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|a coulomb failure stress
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| 653 |
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|a seismic cycle
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| 653 |
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|a tapered Pareto
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| 653 |
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|a seismic prediction
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| 653 |
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|a Technology: general issues / bicssc
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| 653 |
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|a precursors
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| 653 |
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|a earthquake-prone areas
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| 653 |
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|a corner magnitude
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| 653 |
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|a northern and central Apennines
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| 653 |
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|a tidal triggering of earthquakes
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| 653 |
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|a clustering
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| 653 |
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|a Environmental science, engineering and technology / bicssc
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| 653 |
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|a high seismicity criteria
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| 653 |
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|a global seismicity
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| 653 |
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|a system-analytical method
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| 653 |
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|a earthquake clustering
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| 653 |
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|a numerical modeling
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| 653 |
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|a New Zealand
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| 653 |
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|a preparatory phase
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| 653 |
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|a seismicity clustering
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| 653 |
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|a extreme value distribution
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| 653 |
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|a epidemic type aftershock sequence model
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| 653 |
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|a magnitude-frequency distribution
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| 653 |
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|a pattern recognition
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| 653 |
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|a earthquake catalogs
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| 653 |
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|a seismicity patterns
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| 653 |
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|a Bayesian predictive distribution
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| 653 |
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|a DBSCAN algorithm
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| 653 |
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|a statistical methods
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| 700 |
1 |
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|a Giovambattista, Rita Di
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| 700 |
1 |
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|a Shcherbakov, Robert
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| 700 |
1 |
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|a Vallianatos, Filippos
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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| 024 |
8 |
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|a 10.3390/books978-3-0365-4264-5
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| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/87480
|z DOAB: description of the publication
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| 856 |
4 |
0 |
|u https://www.mdpi.com/books/pdfview/book/5678
|7 0
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 363
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| 082 |
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|a 700
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|a 600
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|a 620
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|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.
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