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Book synopsis

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.

Book details

Book category Books in English Technology, engineering, agriculture Civil engineering, surveying & building Building construction & materials

• Full title: Machine Learning in Concrete Technology
• Subtitle: Machine Learning: Concrete Technology
• Author: Pijush Samui, S. K. Sekar, Kallyan Kulkarni
• Language: English
• Binding: Paperback
• Number of pages: 84
• EAN: 9783639356847
• ISBN: 3639356845
• ID: 06842648
• Publisher: VDM Verlag
• Weight: 136 g
• Dimensions: 229 × 152 × 5 mm
• Date of publishing: 11. May 2011

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