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Earthquake Magnitude Prediction in Chile Using Neural Network

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dc.contributor.author Pasari, Sumanta
dc.date.accessioned 2023-08-14T06:53:17Z
dc.date.available 2023-08-14T06:53:17Z
dc.date.issued 2022
dc.identifier.uri https://ieeexplore.ieee.org/document/10054323
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/11369
dc.description.abstract In this study, we implement an earthquake magnitude prediction model using a neural network for a test region in Chile. For this, the epicenter of earthquake is located on a mesh with dimensions of 1°×1°. We adopt a zonation scheme originally proposed by Reyes and Cardenas [1]. The scheme uses increments in b−value and other input parameters to incorporate G-R linear relation and Bath’s law. The model enables the prediction of the maximum magnitude for a given cell within the next five days. Common seismological parameters are used for the performance evaluation of the model. Results show satisfactory performance of the proposed model in comparison to other existing models. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Mathematics en_US
dc.subject Earthquake prediction en_US
dc.subject Neural networks en_US
dc.subject Time-series en_US
dc.title Earthquake Magnitude Prediction in Chile Using Neural Network en_US
dc.type Article en_US


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