E3S Web Conf.
Volume 237, 20213rd International Symposium on Architecture Research Frontiers and Ecological Environment (ARFEE 2020)
|Number of page(s)||5|
|Section||Architecture Science and Civil Engineering|
|Published online||09 February 2021|
Research on prediction of concrete frost resistance based on random forest
School of Civil Engineering & Mechanics, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
2 Wuhan Metro Group Co Ltd, Wuhan, Hubei, 430030, China
3 School of Urban Construction, Wuchang Shouyi University, Wuhan, Hubei, 430074, China
4 School of Civil and Environmental Engineering, Nangyang Technological University, Singapore, 6397898, Singapore
* Corresponding author: firstname.lastname@example.org
Poor frost resistance of concrete will accelerate the deterioration of concrete structure and shorten the service life of concrete. This paper predicts the frost resistance of concrete and selects the initial index of factors that affect the frost resistance of concrete. The random forest algorithm is introduced to remove the unimportant indicators in the initial indicator system of the concrete mix ratio and determine the optimal indicator combination. The relative dynamic elastic modulus is used as the output index of random forest to predict the frost resistance of concrete. The proposed random forest model provides a reasonable and effective method for concrete frost resistance prediction.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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