An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series

An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series

Recently, the study of the coherent noise model has led to a simple (binary) prediction algorithm for the forthcoming earthquake magnitude in aftershock sequences. This algorithm is based on the concept of natural time and exploits the complexity exhibited by the coherent noise model. Here, using th...

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Main Authors: Stavros-Richard G. Christopoulos, Nicholas V. Sarlis
Format: Article
Language:English
Published: Hindawi-Wiley 2017-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2017/6853892
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spelling doaj-1113839224ca42bab81aae03bbe1cc752020-11-24T21:32:11ZengHindawi-WileyComplexity1076-27871099-05262017-01-01201710.1155/2017/68538926853892An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time SeriesStavros-Richard G. Christopoulos0Nicholas V. Sarlis1Faculty of Engineering, Environment and Computing, Coventry University, Priory Street, Coventry CV1 5FB, UKSolid Earth Physics Institute, Department of Physics, School of Science, National and Kapodistrian University of Athens, Panepistimiopolis, Zografos, 157 84 Athens, GreeceRecently, the study of the coherent noise model has led to a simple (binary) prediction algorithm for the forthcoming earthquake magnitude in aftershock sequences. This algorithm is based on the concept of natural time and exploits the complexity exhibited by the coherent noise model. Here, using the relocated catalogue from Southern California Seismic Network for 1981 to June 2011, we evaluate the application of this algorithm for the aftershocks of strong earthquakes of magnitude M≥6. The study is also extended by using the Global Centroid Moment Tensor Project catalogue to the case of the six strongest earthquakes in the Earth during the last almost forty years. The predictor time series exhibits the ubiquitous 1/f noise behavior.http://dx.doi.org/10.1155/2017/6853892
collection DOAJ
language English
format Article
sources DOAJ
author Stavros-Richard G. Christopoulos
Nicholas V. Sarlis
spellingShingle Stavros-Richard G. Christopoulos
Nicholas V. Sarlis
An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series
Complexity
author_facet Stavros-Richard G. Christopoulos
Nicholas V. Sarlis
author_sort Stavros-Richard G. Christopoulos
title An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series
title_short An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series
title_full An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series
title_fullStr An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series
title_full_unstemmed An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series
title_sort application of the coherent noise model for the prediction of aftershock magnitude time series
publisher Hindawi-Wiley
series Complexity
issn 1076-2787
1099-0526
publishDate 2017-01-01
description Recently, the study of the coherent noise model has led to a simple (binary) prediction algorithm for the forthcoming earthquake magnitude in aftershock sequences. This algorithm is based on the concept of natural time and exploits the complexity exhibited by the coherent noise model. Here, using the relocated catalogue from Southern California Seismic Network for 1981 to June 2011, we evaluate the application of this algorithm for the aftershocks of strong earthquakes of magnitude M≥6. The study is also extended by using the Global Centroid Moment Tensor Project catalogue to the case of the six strongest earthquakes in the Earth during the last almost forty years. The predictor time series exhibits the ubiquitous 1/f noise behavior.
url http://dx.doi.org/10.1155/2017/6853892
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