Determination of the Compressive Strength of Concrete Using Artificial Neural Network
Descripción del Articulo
The objective of the work is to estimate the compressive strength of concrete by means of the application of Artificial Neural Networks (ANNs). A database is created with design variables of mixtures of 175, 210, and 280 kgf/cm², which are collected from certified laboratories of soil mechanics and...
| Autor: | |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2024 |
| Institución: | Universidad Nacional de Jaén |
| Repositorio: | UNJ-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorio.unj.edu.pe:UNJ/643 |
| Enlace del recurso: | http://repositorio.unj.edu.pe/handle/UNJ/643 https://doi.org/10.46604/ijeti.2021.7479 |
| Nivel de acceso: | acceso abierto |
| Materia: | Concrete, ANN, artificial neural network, compressive strength https://purl.org/pe-repo/ocde/ford#2.01.00 |
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| dc.title.es_ES.fl_str_mv |
Determination of the Compressive Strength of Concrete Using Artificial Neural Network |
| title |
Determination of the Compressive Strength of Concrete Using Artificial Neural Network |
| spellingShingle |
Determination of the Compressive Strength of Concrete Using Artificial Neural Network Quiñones Huatangari, Lenin Concrete, ANN, artificial neural network, compressive strength https://purl.org/pe-repo/ocde/ford#2.01.00 |
| title_short |
Determination of the Compressive Strength of Concrete Using Artificial Neural Network |
| title_full |
Determination of the Compressive Strength of Concrete Using Artificial Neural Network |
| title_fullStr |
Determination of the Compressive Strength of Concrete Using Artificial Neural Network |
| title_full_unstemmed |
Determination of the Compressive Strength of Concrete Using Artificial Neural Network |
| title_sort |
Determination of the Compressive Strength of Concrete Using Artificial Neural Network |
| author |
Quiñones Huatangari, Lenin |
| author_facet |
Quiñones Huatangari, Lenin |
| author_role |
author |
| dc.contributor.author.fl_str_mv |
Quiñones Huatangari, Lenin |
| dc.subject.es_ES.fl_str_mv |
Concrete, ANN, artificial neural network, compressive strength |
| topic |
Concrete, ANN, artificial neural network, compressive strength https://purl.org/pe-repo/ocde/ford#2.01.00 |
| dc.subject.ocde.es_ES.fl_str_mv |
https://purl.org/pe-repo/ocde/ford#2.01.00 |
| description |
The objective of the work is to estimate the compressive strength of concrete by means of the application of Artificial Neural Networks (ANNs). A database is created with design variables of mixtures of 175, 210, and 280 kgf/cm², which are collected from certified laboratories of soil mechanics and concrete of the city of Jaen. In addition, Weka software is used for the selection of the variables and Matlab software is used for the learning, training, and validation stages of ANNs. Five ANNs are proposed to estimate the compressive strength of concrete at 7th, 14th, and 28th day. The results show that the networks obtain the average error of 4.69% and are composed of an input layer with eleven neurons, two hidden layers with nine neurons each, and the compressive strength of concrete as the output. This method is effective and valid for estimating the compressive strength of concrete as a non-destructive alternative for quality control in the construction industry. |
| publishDate |
2024 |
| dc.date.accessioned.none.fl_str_mv |
2024-04-01T00:26:50Z |
| dc.date.available.none.fl_str_mv |
2024-04-01T00:26:50Z |
| dc.date.issued.fl_str_mv |
2024-03-31 |
| dc.type.es_ES.fl_str_mv |
info:eu-repo/semantics/article |
| dc.type.version.es_ES.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
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article |
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publishedVersion |
| dc.identifier.uri.none.fl_str_mv |
http://repositorio.unj.edu.pe/handle/UNJ/643 |
| dc.identifier.doi.es_ES.fl_str_mv |
https://doi.org/10.46604/ijeti.2021.7479 |
| url |
http://repositorio.unj.edu.pe/handle/UNJ/643 https://doi.org/10.46604/ijeti.2021.7479 |
| dc.language.iso.eng.fl_str_mv |
eng |
| language |
eng |
| dc.relation.es_ES.fl_str_mv |
Determination of the Compressive Strength of Concrete Using Artificial Neural Network |
| dc.relation.ispartof.es_ES.fl_str_mv |
International Journal of Engineering and Technology Innovation International Journal of Engineering and Technology Innovation |
| dc.relation.uri.es_ES.fl_str_mv |
https://doi.org/10.46604/ijeti.2021.7479 |
| dc.rights.es_ES.fl_str_mv |
info:eu-repo/semantics/openAccess |
| dc.rights.uri.es_ES.fl_str_mv |
https://creativecommons.org/licenses/by-nc/4.0/ |
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openAccess |
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https://creativecommons.org/licenses/by-nc/4.0/ |
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application/pdf |
| dc.publisher.es_ES.fl_str_mv |
Universidad Nacional de Jaén |
| dc.publisher.country.es_ES.fl_str_mv |
TW |
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Universidad Nacional de Jaén||Repositorio Institucional – UNJ |
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reponame:UNJ-Institucional instname:Universidad Nacional de Jaén instacron:UNJ |
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UNJ-Institucional |
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http://repositorio.unj.edu.pe/bitstream/UNJ/643/1/ANEXO%2008-5.pdf http://repositorio.unj.edu.pe/bitstream/UNJ/643/2/license.txt |
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Quiñones Huatangari, Lenin2024-04-01T00:26:50Z2024-04-01T00:26:50Z2024-03-31http://repositorio.unj.edu.pe/handle/UNJ/643https://doi.org/10.46604/ijeti.2021.7479The objective of the work is to estimate the compressive strength of concrete by means of the application of Artificial Neural Networks (ANNs). A database is created with design variables of mixtures of 175, 210, and 280 kgf/cm², which are collected from certified laboratories of soil mechanics and concrete of the city of Jaen. In addition, Weka software is used for the selection of the variables and Matlab software is used for the learning, training, and validation stages of ANNs. Five ANNs are proposed to estimate the compressive strength of concrete at 7th, 14th, and 28th day. The results show that the networks obtain the average error of 4.69% and are composed of an input layer with eleven neurons, two hidden layers with nine neurons each, and the compressive strength of concrete as the output. This method is effective and valid for estimating the compressive strength of concrete as a non-destructive alternative for quality control in the construction industry.application/pdfengUniversidad Nacional de JaénTWDetermination of the Compressive Strength of Concrete Using Artificial Neural NetworkInternational Journal of Engineering and Technology InnovationInternational Journal of Engineering and Technology Innovationhttps://doi.org/10.46604/ijeti.2021.7479info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/4.0/Universidad Nacional de Jaén||Repositorio Institucional – UNJreponame:UNJ-Institucionalinstname:Universidad Nacional de Jaéninstacron:UNJConcrete, ANN, artificial neural network, compressive strengthhttps://purl.org/pe-repo/ocde/ford#2.01.00Determination of the Compressive Strength of Concrete Using Artificial Neural Networkinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion42821048ORIGINALANEXO 08-5.pdfANEXO 08-5.pdfapplication/pdf109588http://repositorio.unj.edu.pe/bitstream/UNJ/643/1/ANEXO%2008-5.pdfbd4142374dc1fa5d99f5d3b66979e8cdMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.unj.edu.pe/bitstream/UNJ/643/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52UNJ/643oai:repositorio.unj.edu.pe:UNJ/6432024-08-19 17:57:39.923Repositorio UNJrepositorio@unj.edu.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 |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
