Prediction of Skid Resistance Value of Glass Fiber-Reinforced Tiling Materials
Prediction of Skid Resistance Value of Glass Fiber-Reinforced Tiling Materials
Blog Article
This research focuses on the use of adaptive artificial neural network lock shock and barrel art 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 rosy teacup dogwood 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.