AIJ Journal of Technology and Design
Online ISSN : 1881-8188
Print ISSN : 1341-9463
ISSN-L : 1341-9463
Materials and Construction
PREDICTION OF STRENGTH DEVELOPMENT OF STRUCTURAL CONCRETE USING MACHINE LEARNING
Ryota ISOBESachie SATOYoshitomo YAMADARyuichi HIGA
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2023 Volume 29 Issue 72 Pages 591-596

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Abstract

In this study, we constructed a machine learning model to predict the compressive strength of standard cured specimens and core specimens in high-strength concrete from the material quality, material type, mix proportioning, and construction conditions, in addition to a discussion of factors affecting the strength of the model. The results showed that the machine learning model predicted compressive strength with high accuracy. Furthermore, the effects of factors such as air and maximum temperature of core specimens on the strength were consistent with previous studies, confirming that the model could learn the factors affecting the strength appropriately.

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© 2023, Architectural Institute of Japan
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