基于MATLAB的BP神经网络对特细砂混凝土强度预测的研究

混凝土抗压强度是混凝土最重要的性能之一，是混凝土质量控制最核心的内容。通过介绍混凝土强度的预测方法、BP神经网络预测的过程，在主要考虑水灰比、砂率和水泥用量3个因素的情况下，基于MATLAB用BP神经网络预测特细砂混凝土强度。分析表明：通过BP神经网络模型拟合的计算期望值和实际值的相关系数达到0．96287，相关性非常显著。

Study on the Prediction of Super Fine Sand Concrete Strength by BP Neural Network based on MATLAB

The compressive strength of concrete is one of the most important properties of concrete, and it is the core content of quality control of concrete. This paper explains the concrete strength prediction method, BP neural network prediction, and the prediction of super fine sand concrete strength by BP neural network based on MATLAB taking into account water cement ratio, sand ratio and cement content. Analysis shows that the correlation coefficient of the calculated value using the BP neural network model and the actual value reached 0.96287, which shows that there is a very significant correlation.