Deriving amplification factors from simple site parameters using generalized regression neural networks: implications for relevant site proxies

Deriving amplification factors from simple site parameters using generalized regression neural networks: implications for relevant site proxies

Abstract Most modern seismic codes account for site effects using an amplification factor (AF) that modifies the rock acceleration response spectra in relation to a “site condition proxy,” i.e., a parameter related to the velocity profile at the site under consideration. Therefore, for practical pur...

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Bibliographic Details
Main Authors: Ahmed Boudghene Stambouli, Djawad Zendagui, Pierre-Yves Bard, Boumédiène Derras
Format: Article
Language:English
Published: SpringerOpen 2017-07-01
Series:Earth, Planets and Space
Subjects:
1D linear site response
Site proxies
Amplification factors
Neural network
Online Access:http://link.springer.com/article/10.1186/s40623-017-0686-3

Internet

http://link.springer.com/article/10.1186/s40623-017-0686-3

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