Paper Title:
Prediction for Relative Dynamic Elastic Modulus of PVA-ECC under Freezing and Thawing Cycles
  Abstract

This study focuses on the relative dynamic elastic modulus of the polyvinyl alcohol fiber reinforced cementitious composite (PVA-ECC) after three hundred freeze-thaw cycles. The Artificial Neural Network of freeze-thaw cycles prediction was finally established through data analysis with the help of BP artificial neural network, calculation method optimization and sample training, many times’ trails of the hidden layer and every hidden unit, and the optimal selection of the training function. The results show that there is a small relative error between the predicted value and the actual one of the specimen of the relative dynamic elastic modulus of the PVA-ECC, and the established artificial neural network model bears a higher prediction precision.

  Info
Periodical
Edited by
Ran Chen
Pages
3893-3896
DOI
10.4028/www.scientific.net/AMM.44-47.3893
Citation
H. F. Hou, S. G. Liu, C. W. Yan, J. W. Bai, "Prediction for Relative Dynamic Elastic Modulus of PVA-ECC under Freezing and Thawing Cycles", Applied Mechanics and Materials, Vols. 44-47, pp. 3893-3896, 2011
Online since
December 2010
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