摘要
高强混凝土的强度预测是一个动态性可变复杂问题,受各种因素的影响。采用多种智能方法,建立了高强混凝土的强度预测的遗传算法与神经网络的集成模型。并将该模型计算结果与实测混凝土28 d抗压强度,RBF径向基函数神经网络计算的强度,非线性回归模型计算的强度进行比较。研究表明:预测结果与实测结果吻合较好,较线性回归和神经网络预测精度高,为高强混凝土的强度预测提供了一条新方法。
To make the strength forecast of high strength concrete under influence of several factors exact,the model of Integration of neural network based on genetic algorithms and its learning algorithms are recommended.Then the approach based on Integration of neural network and genetic algorithms is applied to predict the strength of high strength concrete.Furthermore,we contrast it to results of actual measured,the regression,and RBF network It is found that intelligence method can predict the strength of high strength concrete more accurately than the approach of regression does.The result suggests that Integration of neural network based on genetic algorithms is a quantitative and convenient analyzing approach with high accuracy.It is feasible in predicting the strength of high strength concrete.
出处
《混凝土》
CAS
CSCD
北大核心
2010年第10期41-43,共3页
Concrete
关键词
高强混凝土
遗传算法与神经网络的集成模型
强度预测
high strength concrete
integration of neural network based on genetic algorithms
strength forecast
