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为快速准确地预测施工期间拱坝浇筑仓最高温度,基于均匀设计的思想,挑选某在建混凝土拱坝浇筑仓4因素30水平中30组数据进行试验,以浇筑温度、冷却水流量、冷却水水温、环境气温为输入矢量,实测最高温度为输出矢量,构建了混凝土浇筑仓最高温度神经网络智能预测模型,训练后获得了基于均匀设计的混凝土浇筑仓最高温度预测模型。应用结果表明,该预测模型预测值与实测值吻合较好,运算速度快,可快速准确地预测施工现场的混凝土浇筑仓最高温度,特别适用于施工单位现场即时跟踪监测温度变化规律。
In order to predict the maximum temperature of the arch dam during construction quickly and accurately, based on the idea of uniform design, 30 sets of data of 4 factors and 30 levels of the concrete arch dam under construction were selected for testing. The pouring temperature, cooling water flow, cooling water Water temperature and ambient air temperature as input vector and measured maximum temperature as output vector, a neural network intelligent prediction model of maximum temperature of concrete placement silos was constructed. After training, the maximum temperature prediction model of concrete placement silos based on uniform design was obtained. The application results show that the predictive value of the prediction model is in good agreement with the measured value, and the computing speed is fast. The forecasting model can predict the maximum temperature of the concrete placing silos quickly and accurately. It is especially suitable for the on-site tracking and monitoring of the temperature variation of construction units.