Statistics and Pattern Recognition Applied to the Spatio-Temporal Properties of Seismicity

Hae kokoteksti

E-kirja

Gentili, Stefania , Toimittaja

;

Giovambattista, Rita Di , Toimittaja

;

Shcherbakov, Robert , Toimittaja

;

Vallianatos, Filippos , Toimittaja

;

Gentili, Stefania , Muu

;

Giovambattista, Rita Di , Muu

;

Shcherbakov, Robert , Muu

;

Vallianatos, Filippos , Muu

MDPI - Multidisciplinary Digital Publishing Institute 2022

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Ulkoasu

1 electronic resource (180 p.)

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englanti

Alkuteoksen kieli

englanti

Julkaisija

Basel MDPI - Multidisciplinary Digital Publishing Institute, 2022

Aiheet

Technology: general issues

Environmental science, engineering & technology

system-analytical method

earthquake-prone areas

pattern recognition

clustering

machine learning

earthquake catalogs

high seismicity criteria

tidal triggering of earthquakes

seismic cycle

coulomb failure stress

preparatory phase

seismic prediction

earthquake forecasting

precursors

statistical seismology

earthquake likelihood models

seismicity patterns

New Zealand

California

smoothed seismicity methods

global seismicity

foreshocks and aftershocks

earthquake forecasting model

statistical methods

magnitude-frequency distribution

corner magnitude

tapered Pareto

tapered Gutenberg-Richter

epidemic type aftershock sequence model

extreme value distribution

Bayesian predictive distribution

seismicity clustering

DBSCAN algorithm

markovian arrival processes

numerical modeling

earthquake simulator

earthquake clustering

northern and central Apennines

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3-0365-4263-9
3-0365-4264-7

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English

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Statistics and Pattern Recognition Applied to the Spatio-Temporal Properties of Seismicity

Statistics and Pattern Recognition Applied to the Spatio-Temporal Properties of Seismicity

Gentili, Stefania

Giovambattista, Rita Di

Shcherbakov, Robert

Vallianatos, Filippos

Gentili, Stefania

Giovambattista, Rita Di

Shcherbakov, Robert

Vallianatos, Filippos

Technology: general issues

Environmental science, engineering & technology

system-analytical method

earthquake-prone areas

pattern recognition

clustering

machine learning

earthquake catalogs

high seismicity criteria

tidal triggering of earthquakes

seismic cycle

coulomb failure stress

preparatory phase

seismic prediction

earthquake forecasting

precursors

statistical seismology

earthquake likelihood models

seismicity patterns

New Zealand

California

smoothed seismicity methods

global seismicity

foreshocks and aftershocks

earthquake forecasting model

statistical methods

magnitude-frequency distribution

corner magnitude

tapered Pareto

tapered Gutenberg-Richter

epidemic type aftershock sequence model

extreme value distribution

Bayesian predictive distribution

seismicity clustering

DBSCAN algorithm

markovian arrival processes

numerical modeling

earthquake simulator

earthquake clustering

northern and central Apennines

Tämän aineiston tarjoaa

Tämän aineiston tarjoaa