Published in

Freund Publishing House, Science and Engineering of Composite Materials, 1(27), p. 291-298, 2020

DOI: 10.1515/secm-2020-0030



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Statistical Law and Predictive Analysis of Compressive Strength of Cemented Sand and Gravel

Journal article published in 2020 by Shoukai Chen, Yongqiwen Fu, Lei Guo, Shifeng Yang, Yajing Bie
Distributing this paper is prohibited by the publisher
Distributing this paper is prohibited by the publisher

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AbstractA data set of cemented sand and gravel (CSG) mix proportion and 28-day compressive strength was established, with outliers determined and removed based on the Boxplot. Then, the distribution law of compressive strength of CSG was analyzed using the skewness kurtosis and single-sample Kolmogorov-Smirnov tests. And with the help of Python software, a model based on Back Propagation neural network was built to predict the compressive strength of CSG according to its mix proportion. The results showed that the compressive strength follows the normal distribution law, the expected value and variance were 5.471 MPa and 3.962 MPa respectively, and the average relative error was 7.16%, indicating the predictability of compressive strength of CSG and its correlation with the mix proportion.