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Prediction of rubberized concrete properties using artificial neural network and fuzzy logic
AbstractIn this study, waste automobile tyres in two different sizes were used in production of rubberized fresh concretes. Their unit weight and flow table values were determined experimentally. The values determined were also found when artificial neural networks (ANN) and fuzzy logic (FL) models were employed. According to the given rubberized concrete data, it was demonstrated that properties of fresh concrete could be determined without attempting any experiments by using ANN and FL models. During the tests similar results were observed for experimental results with those of ANN and FL models. Besides, the facts that lighter concrete might be produced using tyre as a light material and waste tyres may be recycled this way were put forth.
Prediction of rubberized concrete properties using artificial neural network and fuzzy logic
AbstractIn this study, waste automobile tyres in two different sizes were used in production of rubberized fresh concretes. Their unit weight and flow table values were determined experimentally. The values determined were also found when artificial neural networks (ANN) and fuzzy logic (FL) models were employed. According to the given rubberized concrete data, it was demonstrated that properties of fresh concrete could be determined without attempting any experiments by using ANN and FL models. During the tests similar results were observed for experimental results with those of ANN and FL models. Besides, the facts that lighter concrete might be produced using tyre as a light material and waste tyres may be recycled this way were put forth.
Prediction of rubberized concrete properties using artificial neural network and fuzzy logic
Topçu, İlker Bekir (author) / Sarıdemir, Mustafa (author)
Construction and Building Materials ; 22 ; 532-540
2006-11-20
9 pages
Article (Journal)
Electronic Resource
English
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