Multigene genetic programming for estimation of elastic modulus of concrete

Mohammadi Bayazidi, A; Wang, GG; Bolandi, H; Alavi, AH; Gandomi, AH

Multigene genetic programming for estimation of elastic modulus of concrete

Mohammadi Bayazidi, A Wang, GG Bolandi, H Alavi, AH Gandomi, AH

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Publisher:: HINDAWI LTD
Publication Type:: Journal Article
Citation:: Mathematical Problems in Engineering, 2014, 2014
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Mohammadi Bayazidi, A
dc.contributor.author	Wang, GG
dc.contributor.author	Bolandi, H
dc.contributor.author	Alavi, AH
dc.contributor.author	Gandomi, AH
dc.date.accessioned	2023-03-28T21:22:31Z
dc.date.available	2023-03-28T21:22:31Z
dc.date.issued	2014-01-01
dc.identifier.citation	Mathematical Problems in Engineering, 2014, 2014
dc.identifier.issn	1024-123X
dc.identifier.issn	1563-5147
dc.identifier.uri	http://hdl.handle.net/10453/168752
dc.description.abstract	This paper presents a new multigene genetic programming (MGGP) approach for estimation of elastic modulus of concrete. The MGGP technique models the elastic modulus behavior by integrating the capabilities of standard genetic programming and classical regression. The main aim is to derive precise relationships between the tangent elastic moduli of normal and high strength concrete and the corresponding compressive strength values. Another important contribution of this study is to develop a generalized prediction model for the elastic moduli of both normal and high strength concrete. Numerous concrete compressive strength test results are obtained from the literature to develop the models. A comprehensive comparative study is conducted to verify the performance of the models. The proposed models perform superior to the existing traditional models, as well as those derived using other powerful soft computing tools. © 2014 Alireza Mohammadi Bayazidi et al.
dc.language	English
dc.publisher	HINDAWI LTD
dc.relation.ispartof	Mathematical Problems in Engineering
dc.relation.isbasedon	10.1155/2014/474289
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	01 Mathematical Sciences, 09 Engineering
dc.subject.classification	Numerical & Computational Mathematics
dc.title	Multigene genetic programming for estimation of elastic modulus of concrete
dc.type	Journal Article
utslib.citation.volume	2014
utslib.for	01 Mathematical Sciences
utslib.for	09 Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	open_access	*
dc.date.updated	2023-03-28T21:22:30Z
pubs.publication-status	Published
pubs.volume	2014

Abstract:

This paper presents a new multigene genetic programming (MGGP) approach for estimation of elastic modulus of concrete. The MGGP technique models the elastic modulus behavior by integrating the capabilities of standard genetic programming and classical regression. The main aim is to derive precise relationships between the tangent elastic moduli of normal and high strength concrete and the corresponding compressive strength values. Another important contribution of this study is to develop a generalized prediction model for the elastic moduli of both normal and high strength concrete. Numerous concrete compressive strength test results are obtained from the literature to develop the models. A comprehensive comparative study is conducted to verify the performance of the models. The proposed models perform superior to the existing traditional models, as well as those derived using other powerful soft computing tools. © 2014 Alireza Mohammadi Bayazidi et al.

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http://hdl.handle.net/10453/168752