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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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2017/6853892 |
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| author | Stavros-Richard G. Christopoulos Nicholas V. Sarlis |
| author_facet | Stavros-Richard G. Christopoulos Nicholas V. Sarlis |
| author_sort | Stavros-Richard G. Christopoulos |
| collection | DOAJ |
| 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. |
| format | Article |
| id | doaj-art-1113839224ca42bab81aae03bbe1cc75 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-1113839224ca42bab81aae03bbe1cc752025-02-03T06:13:36ZengWileyComplexity1076-27871099-05262017-01-01201710.1155/2017/68538926853892An 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 |
| spellingShingle | Stavros-Richard G. Christopoulos Nicholas V. Sarlis An Application of the Coherent Noise Model for the Prediction of Aftershock Magnitude Time Series Complexity |
| title | 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_short | 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 |
| url | http://dx.doi.org/10.1155/2017/6853892 |
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