Author:
Tu Jinsong,Liu Yuanzhen,Zhou Ming,Li Ruixia
Abstract
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.
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