Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/14261
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Iruansi, Osimen | - |
dc.contributor.author | Guadagnini, Maurizio | - |
dc.contributor.author | Pilakoutas, Kypros | - |
dc.contributor.author | Neocleous, Kyriacos | - |
dc.date.accessioned | 2019-07-03T05:55:53Z | - |
dc.date.available | 2019-07-03T05:55:53Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | International Journal of Reliability and Safety, 2012, vol.6, no.1-3, pp.82-109 | en_US |
dc.identifier.issn | 14793903 | - |
dc.description.abstract | Advances in neural computing have shown that a neural learning approach that uses Bayesian inference can essentially eliminate the problem of over fitting, which is common with conventional back-propagation neural networks. In addition, Bayesian neural network can provide the confidence (error) associated with its prediction. This paper presents the application of Bayesian learning to train a multilayer perceptron network to predict the shear resistance of reinforced concrete beams without shear reinforcement. The automatic relevance determination technique was employed to assess the relative importance of the different input variables considered in this study on the shear resistance of reinforced concrete beams. The performance of the Bayesian neural network is examined and discussed along with that of current shear design provisions. © 2012 Inderscience Enterprises Ltd. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.relation.ispartof | International Journal of Reliability and Safety | en_US |
dc.subject | Bayesian learning | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Reinforced concrete | en_US |
dc.subject | Shear | en_US |
dc.subject | Uncertainty modelling | en_US |
dc.title | Predicting the Shear Resistance of RC Beams Without Shear Reinforcement Using a Bayesian Neural Network | en_US |
dc.type | Article | en_US |
dc.collaboration | University of Sheffield | en_US |
dc.collaboration | Cyprus University of Technology | en_US |
dc.subject.category | Civil Engineering | en_US |
dc.journals | Subscription | en_US |
dc.country | United Kingdom | en_US |
dc.country | Cyprus | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.1504/IJRS.2012.044299 | en_US |
dc.identifier.scopus | 2-s2.0-84857200810 | - |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/84857200810 | - |
dc.relation.issue | 1-3 | en_US |
dc.relation.volume | 6 | en_US |
cut.common.academicyear | 2011-2012 | en_US |
dc.identifier.spage | 82 | en_US |
dc.identifier.epage | 109 | en_US |
item.fulltext | No Fulltext | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.openairetype | article | - |
item.languageiso639-1 | en | - |
crisitem.journal.journalissn | 1479-3903 | - |
crisitem.journal.publisher | Inderscience | - |
crisitem.author.dept | ERATOSTHENES Centre of Excellence | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0002-2445-5814 | - |
crisitem.author.parentorg | Cyprus University of Technology | - |
Appears in Collections: | Άρθρα/Articles |
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