Yildizel S.Tuskan Y.Kaplan G.2023-04-122023-04-122017-01-0116878086https://hdl.handle.net/20.500.12597/5561This research focuses on the use of adaptive artificial neural network system for evaluating the skid resistance value (British Pendulum Number; BPN) of the glass fiber-reinforced tiling materials. During the creation of the neural model, four main factors were considered: fiber, calcium carbonate content, sand blasting, and polishing properties of the specimens. The model was trained, tested, and compared with the on-site test results. As per the comparison of the outcomes of the study, the analysis and on-site test results showed that there is a great potential for the prediction of BPN of glass fiber-reinforced tiling materials by using developed neural system.trueArticle10.1155/2017/76201872-s2.0-85042098170