| Machine Learning in Concrete Technology Contributor(s): Samui, Pijush (Author), Sekar, S. K. (Author), Kulkarni, Kallyan (Author) |
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ISBN: 3639356845 ISBN-13: 9783639356847 Publisher: VDM Verlag OUR PRICE: $50.27 Product Type: Paperback Published: May 2011 |
| Additional Information |
| BISAC Categories: - Technology & Engineering | Construction - General |
| Physical Information: 0.2" H x 6" W x 9" (0.30 lbs) 84 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |