准确预测特高拱坝混凝土浇筑仓最高温度对其温控防裂具有重要意义。基于RBF神经网络,利用Matlab神经网络工具箱建立了特高拱坝混凝土浇筑仓最高温度预测模型,以浇筑温度、水管布置、通水水温、通水流量及现场环境气温作为输入层,以浇筑仓最高温度为输出层,并通过高温季节、低温季节工程实测数据分别对模型进行验证。结果表明,该模型简单有效、精度高,可满足预测要求。 Accurately predict the maximum temperature of concrete pouring warehouse of UHV arch dam is of great significance to its temperature control and crack prevention. Based on the RBF neural network, the maximum temperature prediction model of the concrete pouring warehouse of UHV arch dam was established by using Matlab neural network toolbox. With the pouring temperature, water pipe arrangement, water temperature, water flow and site ambient temperature as input layer, The highest temperature is the output layer, and through the high temperature season, low temperature seasonal engineering data to verify the model respectively. The results show that the model is simple and effective, high precision and can meet the forecasting requirements.