Abstract
The goal of the study was applying machine learning methods to create rules for prediction of the surface scaling resistance of concrete modified with high-calcium fly ash. To determine the scaling durability the Boras method, according to European Standard procedure (PKN- CEN/TS 12390-9:2007), was used. The results of numeral experiments were utilized as a training set to generate rules indicating the relation between material composition and the scaling resistance. The classifier generated by BFT algorithm from the WEKA workbench can be used as a tool for adequate classification of plain concretes and concretes modified with high-calcium fly ash as materials resistant or not resistant to the surface scaling.
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