Application of BP Neural Network Model in the Recycled Concrete Performance Prediction

DOI

10.2991/aeece-15.2015.106How to use a DOI?

Keywords

Road Engineering; Construction Wastes; Recycled Concrete; BP Neural Network; Concrete Performance; Prediction

Abstract

When the construction wastes were used as raw materials of Recycled concrete, the type and replacement ratio of recycled aggregates should be considered in addition to mix proportion. It is very difficult to describe the complicated nonlinear relationship between different indexes. Through analyzing design process of BP neural network model, the appropriate network parameters were selected, the BP neural network model about performance of recycled concrete is established. After the BP neural network was trained, the 7-20-3 BP neural network model is established to realize nonlinear mapping about performance of recycled concrete. The results show that the established BP network model can accurately predict the recycled concrete slump, 28d compressive strength and elastic modulus, which has a good applicability to the concrete.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jinggan Shao
AU  - Xiaoxiang Ji
AU  - Ran Li
PY  - 2015/09
DA  - 2015/09
TI  - Application of BP Neural Network Model in the Recycled Concrete Performance Prediction
BT  - Proceedings of the International Conference on Advances in Energy, Environment and Chemical Engineering
PB  - Atlantis Press
SP  - 527
EP  - 532
SN  - 2352-5401
UR  - https://doi.org/10.2991/aeece-15.2015.106
DO  - 10.2991/aeece-15.2015.106
ID  - Shao2015/09
ER  -