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Machine Learning in Concrete Technology: Machine Learning: Concrete Technology Kallyan Kulkarni
Machine Learning in Concrete Technology: Machine Learning: Concrete Technology
Kallyan Kulkarni
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.
| Media | Books Paperback Book (Book with soft cover and glued back) |
| Released | May 11, 2011 |
| ISBN13 | 9783639356847 |
| Publishers | VDM Verlag Dr. Müller |
| Pages | 84 |
| Dimensions | 150 × 5 × 226 mm · 136 g |
| Language | English |