An approach for predicting the compressive strength of cement-based materials exposed to sulfate attack.

ABSTRACT: In this paper, a support vector machine (SVM) model which can be used to predict the compressive strength of mortars exposed to sulfate attack was established. An accelerated corrosion test was applied to collect compressive strength data. For predicting the compressive strength of mortars, a total of 638 data samples obtained from experiment was chosen as a dataset to establish a SVM model. The values of the coefficient of determination, the mean absolute error, the mean absolute percentage error and the root mean square error were used for evaluating the predictive accuracy. The main factors affecting the predicted compressive strength were obtained by sensitivity analysis. A SVM model was calibrated, validated, and finally established. Moreover, the performance of the SVM model was comp

SUBMITTER: Chen H 

PROVIDER: S-EPMC5773203 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature