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Proceedings Paper

Autogenous shrinkage prediction on high-performance concrete of fly ash based on BP neural network
Author(s): Baomin Wang; Wenping Zhang; Lijiu Wang
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Paper Abstract

The article adopts test data of neural network for autogenous shrinkage to train and predict on the data which doesn't join training. The article's prediction is on the basis of common medium sand, 5-31.5mm limestone rubble, second class fly-ash, P.O42.5 silicate cement, considering factors include five ones such as ratio of water and cement, sand rate, content of cement, content of fly ash, etc.By adjusting various parameters of neural network structure, it obtains three optimized results of neural network simulation. The error between concrete autogtenous shrinkage value of neural network prediction and trial value is within 3%, which can meet requirement of the concrete engineering.

Paper Details

Date Published: 6 November 2006
PDF: 9 pages
Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63574O (6 November 2006); doi: 10.1117/12.717458
Show Author Affiliations
Baomin Wang, Dalian Univ. of Technology (China)
Wenping Zhang, Dalian Univ. of Technology (China)
Lijiu Wang, Dalian Univ. of Technology (China)


Published in SPIE Proceedings Vol. 6357:
Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence
Jiancheng Fang; Zhongyu Wang, Editor(s)

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