Prediction of Early Compressive Strength of Ultrahigh-Performance Concrete Using Machine Learning Methods
Abstract
In this study, a new prediction model is proposed to predict the 7-day compressive strength of ultrahigh-performance concrete (UHPC) with different mix proportions using artificial neural network (ANN) and support vector machine (SVM). The predicted results are compared with the experimental results to verify the proposed model. Then, the importance of each component and the sensitivity of parameters are investigated. The research proves that the proposed model can estimate the 7-day compressive strength of UHPC based on the mix proportions.
Details
- Organisationseinheit(en)
-
Institut für Photonik
- Externe Organisation(en)
-
Chongqing University
Shanghai Tunnel Engineering Company Ltd.
Wuhan University of Technology
China West Construction Academy of Building Materials
Tongji University
- Typ
- Artikel
- Journal
- International Journal of Computational Methods
- Band
- 20
- Anzahl der Seiten
- 23
- ISSN
- 0219-8762
- Publikationsdatum
- 01.10.2023
- Publikationsstatus
- Veröffentlicht
- Peer-reviewed
- Ja
- ASJC Scopus Sachgebiete
- Informatik (sonstige), Computational Mathematics
- Elektronische Version(en)
-
https://doi.org/10.1142/S0219876221410231 (Zugang:
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