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Simulating the seismic response of embankments via artificial neural networks

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dc.contributor.author Tsompanakis, Y en
dc.contributor.author Lagaros, ND en
dc.contributor.author Psarropoulos, PN en
dc.contributor.author Georgopoulos, EC en
dc.date.accessioned 2014-03-01T01:31:54Z
dc.date.available 2014-03-01T01:31:54Z
dc.date.issued 2009 en
dc.identifier.issn 0965-9978 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/19971
dc.subject Artificial neural networks en
dc.subject Embankments en
dc.subject Material nonlinearity en
dc.subject Seismic response en
dc.subject.classification Computer Science, Interdisciplinary Applications en
dc.subject.classification Computer Science, Software Engineering en
dc.subject.other Accurate predictions en
dc.subject.other Artificial neural networks en
dc.subject.other Design process en
dc.subject.other Earthquake engineerings en
dc.subject.other Equivalent-linear en
dc.subject.other Finite-element methods en
dc.subject.other Geo-materials en
dc.subject.other Geostructures en
dc.subject.other Geotechnical en
dc.subject.other Material nonlinearity en
dc.subject.other Non-linear behaviors en
dc.subject.other SC techniques en
dc.subject.other Science and technologies en
dc.subject.other Time-consuming process en
dc.subject.other Backpropagation en
dc.subject.other Canals en
dc.subject.other Civil engineering en
dc.subject.other Dynamic response en
dc.subject.other Earthquakes en
dc.subject.other Embankments en
dc.subject.other Engineering geology en
dc.subject.other Geotechnical engineering en
dc.subject.other Hydraulic structures en
dc.subject.other Seismic response en
dc.subject.other Soft computing en
dc.subject.other Neural networks en
dc.title Simulating the seismic response of embankments via artificial neural networks en
heal.type journalArticle en
heal.identifier.primary 10.1016/j.advengsoft.2008.11.005 en
heal.identifier.secondary http://dx.doi.org/10.1016/j.advengsoft.2008.11.005 en
heal.language English en
heal.publicationDate 2009 en
heal.abstract Geotechnical earthquake engineering may generally be considered as an ""imprecise"" scientific area due to the unavoidable uncertainties and the simplifications adopted during the design process of geostructures. Therefore, relatively accurate predictions using advanced soft computing (SC) techniques can be tolerated rather than solving a problem conventionally. Artificial neural networks (ANNs), being one of the most popular SC techniques, have been used in many fields of science and technology, as well as, into an increasing number of earthquake engineering applications on structures and infrastructures. In this work the implementation of ANNs is focused on the simulation of the seismic response of a typical embankment. The dynamic response of the embankment is evaluated utilizing the finite-element method, where the nonlinear behavior of the geo-materials can be taken into account by an equivalent-linear procedure. In the present study, this extremely time-consuming process is replaced by properly trained ANNs. © 2008 Elsevier Ltd. All rights reserved. en
heal.publisher ELSEVIER SCI LTD en
heal.journalName Advances in Engineering Software en
dc.identifier.doi 10.1016/j.advengsoft.2008.11.005 en
dc.identifier.isi ISI:000266339000012 en
dc.identifier.volume 40 en
dc.identifier.issue 8 en
dc.identifier.spage 640 en
dc.identifier.epage 651 en


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