Machine Learning in Concrete Technology » książka
Machine Learning in Concrete Technology
ISBN-13: 9783639356847 / Angielski / Miękka / 2011 / 84 str.
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.
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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