This study predicts the capability of recycled plastic granules as a sustainable opportunity to conventional coarse mixture in concrete by using neural network. The goal is to increase a study gadget learning model capable of accurately predicting the compressive strength of concrete containing numerous chances of recycled plastic aggregate. This learning is helpful to overcome the required time period for knowing concrete strength by traditional method. This research contributes imparting a reliable tool for predicting the compressive strength of concrete with plastic combination. It optimize the combination layout for numerous programs, and inspect the effect of various kinds of plastic waste on concrete.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 96 pp. Englisch. N° de réf. du vendeur 9786209604638
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This study predicts the capability of recycled plastic granules as a sustainable opportunity to conventional coarse mixture in concrete by using neural network. The goal is to increase a study gadget learning model capable of accurately predicting the compressive strength of concrete containing numerous chances of recycled plastic aggregate. This learning is helpful to overcome the required time period for knowing concrete strength by traditional method. This research contributes imparting a reliable tool for predicting the compressive strength of concrete with plastic combination. It optimize the combination layout for numerous programs, and inspect the effect of various kinds of plastic waste on concrete.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 96 pp. Englisch. N° de réf. du vendeur 9786209604638
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Taschenbuch. Etat : Neu. Concrete 2.0: Harnessing Machine Learning For Strength Prediction | Machine Learning Algorithm For Strength Prediction of Concrete Second Edition | Venkateswaran S (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209604638 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. N° de réf. du vendeur 134601011
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