Prediction of Impermeability of Concrete Based on Random Forest and Support Vector Machine

Abstract

Abstract: In order to predict the impermeability of concrete quickly and accurately, a RF-SVM prediction model based on random forest (RF) and support vector machine (SVM) was proposed. At first, the permeability coefficient of chloride ion was taken as the evaluation index of impermeability, the initial index system of concrete impermeability was determined based on the ratio of raw materials.Then, the random forest algorithm combined with backward elimination method was used to screen the indexes, and the redundant indexes were eliminated, and the optimal set of indexes for support vector machine modeling was obtained. Finally, a prediction model of concrete impermeability based on support vector machine was established, and a RF-SVM algorithm was developed. Based on a highway project in northeast China, the results show that the proposed RF-SVM model effectively screens out the redundant factors and obtains high precision prediction results, which meets the requirements of engineering practice, and provides a fast and effective method for predicting the impermeability of concrete.

Key words: concrete, impermeability, prediction, random forest, support vector machine, index selection

CLC Number:

TU528

WU Xianguo, LIU Xi, WANG Hongtao, CHEN Hongyu, GAO Fei, HUANG Hanyang. Prediction of Impermeability of Concrete Based on Random Forest and Support Vector Machine[J]. BULLETIN OF THE CHINESE CERAMIC SOCIETY, 2021, 40(3): 829-835.

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