摘要
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 rapidly and accurately predict the concrete pouring block＇s highest temperature during the construction of arch dam, based on uniform design, 30 sets sample data from concrete pouring block＇s 4 factors and 30 levels data of a construction concrete arch dam are chosen to do experiment. Selecting pouring temperature, cooling water flow rate, cooling water temperature and environment temperature as input vectors, the highest measured temperature as output vector, the highest temperature neural network intelligent prediction model of concrete pouring block is established. After training the neural network model, the highest temperature prediction model of concrete pouring block is obtained based on uniform design. Application results show that the model＇s prediction values agree well with the measured values and the operation speed is fast. It can rapidly and accurately predict the highest temperature of concrete pouring block of the construction site. Especially, it is suitable for construction organization to real time monitoring temperature change rule on the construction site.
出处
《水电能源科学》
北大核心
2014年第5期83-85,90,共4页
Water Resources and Power
基金
国家自然科学基金项目(51209124)
关键词
均匀设计
混凝土浇筑仓
最高温度
人工神经网络
预测
uniform design
concrete pouring block
highest temperature
artificial neural network
prediction
作者简介
徐佰林（1989-），男，硕士研究生，研究方向为大坝安全监控，E—mail：xubailin106@163．com
黄耀英（1977-），男，博士、副教授，研究方向为大坝安全监控和结构数值计算，E—mail：huangyaoying@sohu.com.
