ANFIS application to predict the compressive strength of lightweight self-compacting concrete

Vakhshouri, B; Nejadi, S

ANFIS application to predict the compressive strength of lightweight self-compacting concrete

Vakhshouri, B Nejadi, S

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Publication Type:: Conference Proceeding
Citation:: FTC 2016 - Proceedings of Future Technologies Conference, 2017, pp. 28 - 35
Issue Date:: 2017-01-17

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Field	Value	Language
dc.contributor.author	Vakhshouri, B	en_US
dc.contributor.author	Nejadi, S	en_US
dc.date.issued	2017-01-17	en_US
dc.identifier.citation	FTC 2016 - Proceedings of Future Technologies Conference, 2017, pp. 28 - 35	en_US
dc.identifier.isbn	9781509041718	en_US
dc.identifier.uri	http://hdl.handle.net/10453/107765
dc.description.abstract	© 2016 IEEE. Light-weight Self-Compacting Concrete (LWSCC) might be the answer to the increasing construction requirements of slenderer and more heavily reinforced structural elements. However there are limited studies to prove its ability in real construction projects. In conjunction with the traditional methods, artificial intelligent based modeling methods have been applied to simulate the non-linear and complex behavior of concrete in the recent years. Twenty one laboratory experimental investigations on the mechanical properties of LWSCC; published in recent 12 years have been analyzed in this study. The collected information is used to investigate the relationship between compressive strength, elasticity modulus and splitting tensile strength in LWSCC. Analytically proposed model in ANFIS is verified by multi factor linear regression analysis. Comparing the estimated results, ANFIS analysis gives more compatible results and is preferred to estimate the properties of LWSCC.	en_US
dc.relation.ispartof	FTC 2016 - Proceedings of Future Technologies Conference	en_US
dc.relation.isbasedon	10.1109/FTC.2016.7821586	en_US
dc.title	ANFIS application to predict the compressive strength of lightweight self-compacting concrete	en_US
dc.type	Conference Proceeding
utslib.for	0905 Civil Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2016 IEEE. Light-weight Self-Compacting Concrete (LWSCC) might be the answer to the increasing construction requirements of slenderer and more heavily reinforced structural elements. However there are limited studies to prove its ability in real construction projects. In conjunction with the traditional methods, artificial intelligent based modeling methods have been applied to simulate the non-linear and complex behavior of concrete in the recent years. Twenty one laboratory experimental investigations on the mechanical properties of LWSCC; published in recent 12 years have been analyzed in this study. The collected information is used to investigate the relationship between compressive strength, elasticity modulus and splitting tensile strength in LWSCC. Analytically proposed model in ANFIS is verified by multi factor linear regression analysis. Comparing the estimated results, ANFIS analysis gives more compatible results and is preferred to estimate the properties of LWSCC.

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http://hdl.handle.net/10453/107765