当前位置：
X-MOL 学术
›
Proc. Inst. Mech. Eng. Part F: J. Rail Rapid Transit
›
论文详情
Our official English website, www.x-mol.net, welcomes your
feedback! (Note: you will need to create a separate account there.)
Machine learning based prediction of rail transit signal failure: A case study in the United States
Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit ( IF 1.7 ) Pub Date : 2022-09-23 , DOI: 10.1177/09544097221127781 Junyan Dai 1 , Xiang Liu 1
Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit ( IF 1.7 ) Pub Date : 2022-09-23 , DOI: 10.1177/09544097221127781 Junyan Dai 1 , Xiang Liu 1
Affiliation
Signals are an important part of the urban rail transit system. Signals being in functioning condition is key to rail transit safety. Predicting rail transit signal failures ahead of time has signi...
中文翻译：
基于机器学习的轨道交通信号故障预测：美国案例研究
信号是城市轨道交通系统的重要组成部分。信号正常运行是轨道交通安全的关键。提前预测轨道交通信号故障具有重要意义...
更新日期：2022-09-25
中文翻译：
基于机器学习的轨道交通信号故障预测：美国案例研究
信号是城市轨道交通系统的重要组成部分。信号正常运行是轨道交通安全的关键。提前预测轨道交通信号故障具有重要意义...
京公网安备 11010802027423号