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Earthquake Engineering Problems in Parallel Neuro Environment

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dc.contributor.author Barai, Sudhir Kumar
dc.date.accessioned 2021-11-27T04:16:52Z
dc.date.available 2021-11-27T04:16:52Z
dc.date.issued 2019
dc.identifier.uri https://link.springer.com/chapter/10.1007/978-3-540-30474-6_25
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/3696
dc.description.abstract The aim of the paper is to explore the application of Parallel Neuro Simulator for the generation of artificial earthquake. Parallel Neuro Simulator is a neural network code developed on PARAM 10000 using ‘C’ language and MPI library subroutines. In this study, two artificial neural network (ANN) models have been proposed to replace the auto-regressive moving average (ARMA) model. First ANN model substitutes the polynomial model that represents the relation of initial site information and coefficients of polynomial and the second ANN based model substitutes the estimated parameters of the ARMA model. Several Indian earthquake records have been used for present study on PARAM 10000. The variation in computational time with increasing number of processors has also been studied. en_US
dc.language.iso en en_US
dc.publisher Springer en_US
dc.subject Civil Engineering en_US
dc.subject Ground Motion en_US
dc.subject Artificial Neural Network en_US
dc.subject Neural Network Model en_US
dc.subject Artificial Neural Network Model en_US
dc.subject Message Passing Interface en_US
dc.title Earthquake Engineering Problems in Parallel Neuro Environment en_US
dc.type Book chapter en_US


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