摘要
文章以武汉地铁6号线前进村为例,结合前进村站的实际客流量与设计客流量以及我国C级服务水平地铁站,构建了基于BP神经网络的地铁造价估算模型,对该地铁站的造价进行了预测,将预测值和真实造价值进行对比,对于优化地铁结构设计,合理控制地铁造价,提出了合理的建议。
Taking the Qianjin Village of Wuhan Metro Line 6 as an example, combined with the actual passenger flow and design passenger flow of Qianjin Village Station and China's C-class service level subway station, a subway cost estimation model based on BP neural network was constructed, and the cost of the subway station was built. The predictions were made to compare the predicted values with the real value. The reasonable suggestions for optimizing the subway structure design and controlling the cost of the subway were put forward.
引文
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[2]赵欣.基于BP神经网络的地铁土建工程造价估算方法研究[D].北京交通大学,2008.
[3]王元丰,许丽丽,高婧.客流预测量对地铁车站造价的影响分析[J].城市轨道交通研究,2008(7):35-38.