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Machine learning techniques applied to construction: A hybrid bibliometric analysis of advances and future directions

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Machine learning techniques applied to construction: A hybrid bibliometric analysis of advances and future directions

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García, J.; Villavicencio, G.; Altimiras, F.; Crawford, B.; Soto, R.; Minatogawa, V.; Franco, M.... (2022). Machine learning techniques applied to construction: A hybrid bibliometric analysis of advances and future directions. Automation in Construction. 142:1-22. https://doi.org/10.1016/j.autcon.2022.104532

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/190067

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Title: Machine learning techniques applied to construction: A hybrid bibliometric analysis of advances and future directions
Author: García, Jose Villavicencio, Gabriel Altimiras, Francisco Crawford, Broderick Soto, Ricardo Minatogawa, Vinicius Franco, Matheus Martínez-Muñoz, D. Yepes, V.
UPV Unit: Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Caminos, Canales y Puertos - Escola Tècnica Superior d'Enginyers de Camins, Canals i Ports
Issued date:
Embargo end date: 2024-10-31
Abstract:
[EN] Complex industrial problems coupled with the availability of a more robust computing infrastructure present many challenges and opportunities for machine learning (ML) in the construction industry. This paper reviews ...[+]
Subjects: Machine learning , BERT , Construction , Concretes , Retaining walls , Tunnels , Pavements , Construction management
Copyrigths: Embargado
Source:
Automation in Construction. (issn: 0926-5805 )
DOI: 10.1016/j.autcon.2022.104532
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.autcon.2022.104532
Project ID:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-117056RB-I00/ES/OPTIMIZACION HIBRIDA DEL CICLO DE VIDA DE PUENTES Y ESTRUCTURAS MIXTAS Y MODULARES DE ALTA EFICIENCIA SOCIAL Y MEDIOAMBIENTAL BAJO PRESUPUESTOS RESTRICTIVOS/
info:eu-repo/grantAgreement/CONICYT//1210810/
info:eu-repo/grantAgreement/FONDECYT//11180056//Concurso Iniciación en Investigación/
info:eu-repo/grantAgreement/PUCV//039414%2F2021/
Thanks:
The authors gratefully acknowledge the funding received from the following research projects: Jose Garcia was supported by the Grant CONICYT/FONDECYT/INICIACION/, Chile 11180056. Jose Garcia and Vinicius Minatogawa was ...[+]
Type: Artículo

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