摘要
将灰色关联分析法应用于南京地铁列车,对影响其牵引能耗的因素重要度进行排序,并利用能耗测量数据建立基于BP神经网络学习与预测模型,通过对该模型精确度进行反复校验,从而实现南京地铁牵引能耗的准确预测。
This paper applies grey relational analysis to Nanjing metro,ranks the importance of the factors affecting the traction energy consumption,and uses energy consumption data to establish the BP-based neural network learning and prediction model.By repeatedly verifying the accuracy of the model,the accurate prediction of the traction energy consumption of Nanjing metro can be achieved.
作者
张学兵
胡文斌
哈进兵
丁义帅
褚蓄
Zhang Xuebing;Hu Wenbin;Ha Jinbing;Ding Yishuai;Chu Xu(Nanjing Metro Operation Co.,Ltd.,Nanjing 210012,China;Nanjing University of Science and Technology,Nanjing 210014,China)
出处
《铁路通信信号工程技术》
2020年第12期51-56,共6页
Railway Signalling & Communication Engineering
关键词
地铁牵引能耗
影响因素
灰色关联分析
BP神经网络
预测模型
energy consumption of metro traction
affecting factors
grey relational analysis
BP neural network
prediction model
