人工神经网络在混凝土强度预测中的应用

人工神经网络技术综合考虑了高强度、高性能混凝土强度的各种影响因素,可用于预测混凝土强度。本文选取混凝土配料中7个因素作为输入值,混凝土28d强度作为输出值,建立起混凝土强度预测BP网络模型,进而对混凝土配合比强度实验数据进行分析预测,结果效果良好。表明该方法用于高性能混凝土强度预测方面是可行的。

Application of Artificial Neural Network in the Prediction of the Compression Strength of Concrete

A new technique of nondestructively assessing the compression strength of concrete which employs (artificial) neural networks, is presented. Because main factors of influencing high strength and high performance concrete strength are considered. Artificial neural network can deal with non-line problem and forecast strength. In this paper BP artificial neural network is presented. This prediction model is based on BP artificial neural network with 7 influencing (factors) as input parameters and 28d strength as output one. The analysis and test on datum about mixed ration and strength of concrete have been performed, too. The results show it is very useful to predict the strength of concrete in these (methods) and will has a good future for the optimal strength prediction of high performance concrete.