Prediction and analysis of compressive strength of recycled aggregate thermal insulation concrete based on GA-BP optimization network
2020 ◽
Vol ahead-of-print
(ahead-of-print)
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Keyword(s):
Purpose This paper aims to predict the 28-day compressive strength of recycled thermal insulation concrete more accurately. Design/methodology/approach The initial weights and thresholds of BP neural network are improved by genetic algorithm on MATLAB 2014 a platform. Findings Genetic algorithm–back propagation (GA-BP) neural network is more stable. The generalization performance of the complex is better. Originality/value The GA-BP neural network based on the training sample data can better realize the strength prediction of recycled aggregate thermal insulation concrete and reduce the complex orthogonal experimental process. GA-BP neural network is more stable. The generalization performance of the complex is better.
2010 ◽
Vol 29-32
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pp. 1543-1549
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2017 ◽
Vol 14
(2)
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pp. 155-158
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Keyword(s):
2013 ◽
Vol 333-335
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pp. 856-859
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2019 ◽
Vol 18
(3)
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pp. 601-609
Keyword(s):
2019 ◽
Vol 10
(04)
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pp. 1950024
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