Prediction and analysis of compressive strength of recycled aggregate thermal insulation concrete based on GA-BP optimization network

PurposeThis paper aims to predict the 28-day compressive strength of recycled thermal insulation concrete more accurately.Design/methodology/approachThe initial weights and thresholds of BP neural network are improved by genetic algorithm on MATLAB 2014 a platform.FindingsGenetic algorithm–back propagation (GA-BP) neural network is more stable. The generalization performance of the complex is better.Originality/valueThe 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.