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Araştırma Çıktıları | Web Of Science
Web of Science Koleksiyonu
English
English
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Date
Authors
Yildizel, SA
Tuskan, Y
Kaplan, G
Journal Title
Journal ISSN
Volume Title
Publisher
1687-8086
Abstract
HINDAWI LTD
Description
Keywords
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.
Citation
URI
http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/6903
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Web of Science Koleksiyonu
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