The determination of Elastic Modulus (E) of normal strength concrete is an important task in civil engineering for infrastructure development. Experimental methods for determination of E value of normal strength concrete are complicated and time consuming. This article employs an Artificial Intelligence (AI) technique for prediction of E value of normal strength concrete. The results are compared with a widely used Artificial Neural Network (ANN), Support Vector Machine (SVM) model and empirical equation from the different buildings codes. Equations have been also developed for determination of E value of normal strength concrete based on the AI. The developed AI model also gives error bar of predicted E value. The predicted error bar can be used to determine model uncertainty. This study shows that the developed AI is a robust model for prediction of E value of normal strength concrete.
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Dr. Pijush Samui is an associate professor at CDMM in VIT University, Vellore, India. Dr. S.K. Sekar is the director of CDMM in VIT University. Kallyan Kulkarni is a postgraduate student at VIT university
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Samui PijushDr. Pijush Samui is an associate professor at CDMM in VIT University, Vellore, India. Dr. S.K. Sekar is the director of CDMM in VIT University. Kallyan Kulkarni is a postgraduate student at VIT universityAutor. Seller Inventory # 4980534
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The determination of Elastic Modulus (E) of normal strength concrete is an important task in civil engineering for infrastructure development. Experimental methods for determination of E value of normal strength concrete are complicated and time consuming. This article employs an Artificial Intelligence (AI) technique for prediction of E value of normal strength concrete. The results are compared with a widely used Artificial Neural Network (ANN), Support Vector Machine (SVM) model and empirical equation from the different buildings codes. Equations have been also developed for determination of E value of normal strength concrete based on the AI. The developed AI model also gives error bar of predicted E value. The predicted error bar can be used to determine model uncertainty. This study shows that the developed AI is a robust model for prediction of E value of normal strength concrete. Seller Inventory # 9783639356847
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Taschenbuch. Condition: Neu. Machine Learning in Concrete Technology | Machine Learning: Concrete Technology | Pijush Samui (u. a.) | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639356847 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 107008434
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