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为了克服混凝土施工中强度评定滞后现象,提出采用BP神经网络技术进行粉煤灰混凝土早期强度预测。通过粉煤灰混凝土正交试验,并对实验结果进行极差分析,找出影响粉煤灰混凝土强度的主次要因素,进而作为BP神经网络输入参数,预测粉煤灰混凝土的抗压与抗折强度。经过预测值与实测值对比分析,结果表明BP神经网络技术有很好的预测精度。应用BP神经网络技术对混凝土施工中的质量状况及时预报,有重要的技术应用价值。
In order to overcome the lag of strength evaluation in concrete construction, the prediction of early strength of fly-ash concrete by BP neural network is proposed. Through the orthogonal experiment of fly ash concrete and the range analysis of the experimental results, the main and secondary factors influencing the strength of fly ash concrete are found out, and then the input parameters of BP neural network are used to predict the compressive strength and anti-stress of fly ash concrete Breaking strength. After comparing the predicted value with the measured value, the results show that the BP neural network technology has a good prediction accuracy. Application of BP neural network technology in the construction of concrete quality status in a timely manner forecast, there are important technical value.