Machine Learning in Concrete Technology: Machine Learning: Concrete Technology

Samui, Pijush, Sekar, S.K., Kulkarni, Kallyan

ISBN 10: 3639356845 / ISBN 13: 9783639356847

Editore: VDM Verlag Dr. Müller, 2011

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Codice articolo ERICA75836393568456

Dati bibliografici

• Titolo: Machine Learning in Concrete Technology: Machine Learning: Concrete Technology
• Editore: VDM Verlag Dr. Müller
• Data di pubblicazione: 2011
• Lingua: Inglese
• ISBN 10: 3639356845
• ISBN 13: 9783639356847
• Rilegatura: Paperback
• Condizione: Like New
• Tipo di libro: book

Descrizione articolo

Riassunto

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.

L'autore

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