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Application of Artificial Neural Networks To Determine Concrete Compressive Strength Based on Non-destructive Tests

Author(s):

Medium: journal article
Language(s): Latvian
Published in: Journal of Civil Engineering and Management, , n. 1, v. 11
Page(s): 23-32
DOI: 10.3846/13923730.2005.9636329
Abstract:

The paper deals with the neural identification of the compressive strength of concrete on the basis of non‐destructively determined parameters. Basic information on artificial neural networks and the types of artificial neural networks most suitable for the analysis of experimental results are given. A set of experimental data for the training and testing of neural networks is described. The data set covers a concrete compressive strength ranging from 24 to 105 MPa. The methodology of the neural identification of compressive strength is presented. Results of such identification are reported. The results show that artificial neural networks are highly suitable for assessing the compressive strength of concrete. The neural identification of the compressive strength of concrete has been verified in situ.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.3846/13923730.2005.9636329.
  • About this
    data sheet
  • Reference-ID
    10363332
  • Published on:
    12/08/2019
  • Last updated on:
    12/08/2019
 
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