Are northeast and western Himalayas earthquake dynamics better "organized" than Central Himalayas: An artificial neural network approach
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| Formato: | Artículo científico |
| Lenguaje: | en |
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Universidad Nacional Autónoma de México
2007
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| _version_ | 1876439515486224384 |
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| author | S. Sri Lakshmi |
| author_facet | S. Sri Lakshmi |
| contents | Are northeast and western Himalayas earthquake dynamics better "organized" than Central Himalayas: An artificial neural network approach S. Sri Lakshmi R. K. Tiwari Ciencias de la Tierra self Himalaya seismicity organisation neural networks The Himalaya covering 20-38° N latitude and 70-98° E longitude, is one of the most seismo-tectonically active and vulnerableregions of the world. Visual inspection of the temporal earthquake frequency pattern of the Himalayas indicates the nature of thetectonic activity prevailing in this region. However, the quantifi cation of this dynamical pattern is essential for constraining amodel and characterizing the nature of earthquake dynamics in this region. We examine the temporal evolution of seismicity (M≥ 4) of the Central Himalaya (CH), Western Himalaya (WH) and Northeast Himalaya (NEH), for the period of 1960-2003 usingartifi cial neural network (ANN) technique. We use a multilayer feedforward artifi cial neural network (ANN) model to simulatemonthly resolution earthquake frequency time series for all three regions. The ANN is trained using a standard back-propagationalgorithm with gradient decent optimization technique and then generalized through cross-validation. The results suggest thatearthquake processes in all three regions evolved on a high dimensional chaotic plane akin to self-organized dynamical pattern.Earthquake processes of NEH and WH show a higher predictive correlation coeffi cient (50-55%) compared to the CH (30%),implying that the earthquake dynamics in the NEH and WH are better organized than in the CH region. The available tectonogeologicalobservations support the model predictions. 2007 artículo científico 0016-7169 https://www.redalyc.org/articulo.oa?id=56846104 en http://www.redalyc.org/revista.oa?id=568 Geofísica Internacional application/pdf Universidad Nacional Autónoma de México Geofísica Internacional (México) Num.1 Vol.46 |
| format | Artículo científico |
| id | redalyc_56846104 |
| institution | Redalyc |
| language | en |
| publishDate | 2007 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Are northeast and western Himalayas earthquake dynamics better "organized" than Central Himalayas: An artificial neural network approach S. Sri Lakshmi Ciencias de la Tierra self Himalaya seismicity organisation neural networks Are northeast and western Himalayas earthquake dynamics better "organized" than Central Himalayas: An artificial neural network approach S. Sri Lakshmi R. K. Tiwari Ciencias de la Tierra self Himalaya seismicity organisation neural networks The Himalaya covering 20-38° N latitude and 70-98° E longitude, is one of the most seismo-tectonically active and vulnerableregions of the world. Visual inspection of the temporal earthquake frequency pattern of the Himalayas indicates the nature of thetectonic activity prevailing in this region. However, the quantifi cation of this dynamical pattern is essential for constraining amodel and characterizing the nature of earthquake dynamics in this region. We examine the temporal evolution of seismicity (M≥ 4) of the Central Himalaya (CH), Western Himalaya (WH) and Northeast Himalaya (NEH), for the period of 1960-2003 usingartifi cial neural network (ANN) technique. We use a multilayer feedforward artifi cial neural network (ANN) model to simulatemonthly resolution earthquake frequency time series for all three regions. The ANN is trained using a standard back-propagationalgorithm with gradient decent optimization technique and then generalized through cross-validation. The results suggest thatearthquake processes in all three regions evolved on a high dimensional chaotic plane akin to self-organized dynamical pattern.Earthquake processes of NEH and WH show a higher predictive correlation coeffi cient (50-55%) compared to the CH (30%),implying that the earthquake dynamics in the NEH and WH are better organized than in the CH region. The available tectonogeologicalobservations support the model predictions. 2007 artículo científico 0016-7169 https://www.redalyc.org/articulo.oa?id=56846104 en http://www.redalyc.org/revista.oa?id=568 Geofísica Internacional application/pdf Universidad Nacional Autónoma de México Geofísica Internacional (México) Num.1 Vol.46 |
| title | Are northeast and western Himalayas earthquake dynamics better "organized" than Central Himalayas: An artificial neural network approach |
| topic | Ciencias de la Tierra self Himalaya seismicity organisation neural networks |
| url | https://www.redalyc.org/articulo.oa?id=56846104 |