This 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.
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Nous voudrions effectuer une description ici mais le site que vous consultez ne nous en laisse pas la possibilité. from #AlexandrosSfakian...
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Radiation Research, Volume 187, Issue 6 , Page 647-658, June 2017. from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader ...
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