基于BP网络的水泥强度预测

运用改进的BP算法,建立了水泥强度预测模型.模型1用于预测水泥抗压强度,网络输入为水泥3 d抗压强度,网络输出为水泥28 d抗压强度;模型2用于预测水泥抗折强度,网络输入为水泥3 d抗折强度,网络输出为水泥28 d抗折强度.网络的改进主要采用附加冲量和自适应学习率等方法,网络运行良好.模型1的相对误差平均值为1.665 5%;模型2的相对误差平均值为3.834 1%,预测结果较为理想.

Prediction Based on BP Network for Cement Strength

Based on optimized BP algorithms, some prediction models are developed for cement strength. The model 1 is used to predict compression strength, of which the input is 3 d compression strength and the output is 28 d compression strength. The model 2 is used to predict bending strength, of which the input is 3 d bending strength and the output is 28 d bending strength. The BP algorithms covering additional momentum and adaptive learning rate taken to optimize the proposed BP network, which thus works efficiently. The mean values of relative errors of model 1 and model 2 are 1.6655% and 3.8341%, respectively, and the results of the prediction are proved close to the experimental ones.