地铁车站侧墙混凝土裂缝影响因素分析及控制研究

以南昌地铁2号线某车站侧墙混凝土裂缝数为研究对象，以BP神经网络进行训练，计算各因素对侧墙混凝土裂缝的平均影响值（MIV），构建MIV-BP神经网络模型，实证分析各因素对侧墙混凝土裂缝的影响作用程度。结果表明:保护层过薄、混凝土分块过大和混凝土配合比不合理是造成侧墙混凝土裂缝的主要影响因素，而其他因素为次要原因。

The Influence Factors Analysis and Control Research on Side Wall Concrete Crack of Subway Station

Taking the side wall concrete crack number a the stalion on No.2 Line of Nanchang subway as the research object, train the BP neural network to calculate MIV of the factors influencing on side wall concrete crack, build MIV-BP neural network model and empirically analyze the effect of the factors on side wall concrete cracks. The results show that the too thin protective layer, too large concrete block and unreasonable concrete mixing proportion are the main influence factors of side wall concrete crack and other factors are secondary causes.