This research focuses on the use of adaptive artificial neural network system for evaluating the skid resistance value (British\nPendulum Number; BPN) of the glass fiber-reinforced tiling materials. During the creation of the neural model, four main factors\nwere considered: fiber, calcium carbonate content, sand blasting, and polishing properties of the specimens. The model was\ntrained, tested, and compared with the on-site test results. As per the comparison of the outcomes of the study, the analysis and\non-site test results showed that there is a great potential for the prediction of BPN of glass fiber-reinforced tiling materials by using\ndeveloped neural system.
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