Neural Network-Based Estimation of Strong Ground Motion Parameters

Language: English

Published by LAP LAMBERT Academic Publishing, 2013

3659275050 / 9783659275050

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - Seismic evaluation of existing facilities and design of earthquake-resistant structures requires estimation of strong ground motion parameters. Ground motion prediction equations are derived for estimating strong ground motion parameters. Traditionally, ground motion prediction equations are developed using statistical regression analyses. This book presents a very promising application of the powerful and versatile neural network approach to the derivation of ground motion prediction equations using Japanese earthquake records and site characteristics. Multi-layer perceptron neural network models with back-propagation learning scheme have been developed to predict strong ground motion parameters that are of primary significance in earthquake engineering using the actual seismic data without any simplification and assumptions. Statistics of the results presented indicate that artificial neural network is capable of learning and representing the local variations quite accurately. This book is intended to help structural engineers in selection of appropriate characterization of ground motion for engineering applications that are used in seismic analysis and design.

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Title
Neural Network-Based Estimation of Strong Ground Motion Parameters
Author
Arjun C . R.
Publisher
LAP LAMBERT Academic Publishing
Publication year
2013
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3659275050
ISBN 13
9783659275050
Item weight
149 grams
Dimensions
220x150x6 mm

AHA-BUCH GmbH

Einbeck, Germany

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