A data-driven artificial neural network model for the prediction of ground motion from induced seismicity: The case of The Geysers geothermal field

A data-driven artificial neural network model for the prediction of ground motion from induced seismicity: The case of The Geysers geothermal field

Ground-motion models have gained foremost attention during recent years for being capable of predicting ground-motion intensity levels for future seismic scenarios. They are a key element for estimating seismic hazard and always demand timely refinement in order to improve the reliability of seismic...

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Bibliographic Details
Main Authors: Edoardo Prezioso, Nitin Sharma, Francesco Piccialli, Vincenzo Convertito
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-11-01
Series:Frontiers in Earth Science
Subjects:
ground motion
neural network
induced seismic activity
data-driven model
geothermal field applications
Online Access:https://www.frontiersin.org/articles/10.3389/feart.2022.917608/full

Internet

https://www.frontiersin.org/articles/10.3389/feart.2022.917608/full

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