Prediction of fracture parameters of concrete by Artificial Neural Networks

dc.contributor.authorInce, R
dc.date.accessioned2026-08-12T17:43:36Z
dc.date.issued2004
dc.departmentFırat Üniversitesi
dc.description.abstractModelling of material behaviour generally involves the development of a mathematical model derived from observations and experimental data. An alternative way discussed in this paper is Artificial Neural Network (ANN)-based modelling which is a subfield of artificial intelligence. The main benefit in using an ANN approach is that the network is built directly from experimental data using the self-organising capabilities of the ANN. In this paper the Two-Parameter Model (TPM) in the fracture of cementitious materials is modelled with a back-propagation ANN. The results of an ANN-based TPM look viable and very promising. (C) 2004 Elsevier Ltd. All rights reserved.
dc.identifier.doi10.1016/j.engfracmech.2003.12.004
dc.identifier.endpage2159
dc.identifier.issn0013-7944
dc.identifier.issn1873-7315
dc.identifier.issue15
dc.identifier.orcid0000-0002-9837-8284
dc.identifier.scopus2-s2.0-2142827946
dc.identifier.scopusqualityQ1
dc.identifier.startpage2143
dc.identifier.urihttps://doi.org/10.1016/j.engfracmech.2003.12.004
dc.identifier.urihttps://hdl.handle.net/11508/60199
dc.identifier.volume71
dc.identifier.wosWOS:000221991300003
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltd
dc.relation.ispartofEngineering Fracture Mechanics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260511
dc.subjectconcrete
dc.subjectfracture mechanics
dc.subjecttwo-parameter model
dc.subjectartificial intelligence
dc.subjectartificial neural networks
dc.titlePrediction of fracture parameters of concrete by Artificial Neural Networks
dc.typeArticle

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