Compressive strength prediction of ultra high performance concrete incorporated with coarse aggregates based on GA-BP neural network
In order to predict the compressive strength and to optimize the mix design of ultra high performance concrete(UHPC)incorporated with coarse aggregates,168 mix proportions and corresponding compressive strength of UHPC after 28 days standard curing were collected from domestic and foreign literature.Charts of frequency distribution of each material component and compressive strength were given,and correlations between each material component and compressive strength were analyzed based on grey relational analysis(GRA)method.Through parameter analysis,the back propagation(BP)neural network based on genetic algorithm(GA)was established,which achieved better prediction accuracy and generalization ability than common BP neural network.Finally,based on the established GA-BP neural network,the recommended ranges of coarse aggregates-binder ratio,volume fraction of steel fiber and sand-binder ratio were given in the mix design for preparing UHPC incorporated with coarse aggregates of different strength grades.
ultra high performance concrete(UHPC)compressive strengthcoarse aggregatesback propagation neural networkgenetic algorithm
万方数据
维普
