Lightweight Concrete Strength Prediction by BP-ANN

Abstract:

The back propagation artificial neural networks (BP-ANN) use a resilient back-propagation algorithm and early stopping technique. By inputing the properties of geometries and material, NNs can predict the strength of lightweight concrete. An BP-ANN model based on feed-forward neural network is built, trained and tested using the available test data of 148 mix records collected from the technical literature. And the test results are compared and analyzed with experimental data . It shows that the strength of lightweight concrete obtained by the simplified model based on NNs are in good agreement with test results, and they are close to the experimental values. The NNs model can be used in the shear strength prediction and design for the strength of lightweight concrete.

• Periodical: Advanced Materials Research (Volume 1090)
• Pages: 101-106
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1090.101
• Online since: February 2015
• Authors: Kai Huang*, Cheng Wei Zhong
• Keywords: Concrete, Lightweight Aggregate, Neural Network, Strength

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