气膜薄壳钢筋混凝土穹顶储仓的施工工期预测研究  

Research on Forecasting of Project Duration on Thin-shell Concrete Dome Using Inflated Forms

作　　者：李万庆[1] 岳丽飞 孟文清[2] 陈盼盼[1] 

机构地区：[1]河北工程大学经济管理学院,邯郸056038 [2]河北工程大学土木工程学院,邯郸056038

出　　处：《价值工程》2015年第28期52-54,共3页Value Engineering

摘　　要：根据气膜薄壳钢筋混凝土穹顶储仓的施工特点,详细分析了影响其施工工期的因素及参数获取方式,结合灰色GM(1,1)模型和BP神经网络处理数据的优点,提出了基于串联型灰色神经网络(serial grey neural network,SGNN)的施工工期预测模型并进行预测仿真。结果表明:该方法切实可行,预测精度高于GM(1,1)方法。According to the construction characteristics of concrete thin-shell domes using inflated forms, this paper analyzes the factors affecting project duration and it presents a new forcasting system of project duration （serial grey neural network）, which integrates the data processing advantage of GM （1,1） and BP neural network. The perforamance is demonstrated by using MATLAB software. The results show that the approach is feasible and effective in comparison with single model GM（1,1）.

关 键 词：气膜 薄壳 串联型灰色神经网络 施工工期 预测 

分 类 号：TU722[建筑科学—建筑技术科学]