TY  - JOUR
PY  - 2022//
TI  - A high-speed railway network dataset from train operation records and weather data
JO  - Scientific data
A1  - Zhang, Dalin
A1  - Peng, Yunjuan
A1  - Xu, Yi
A1  - Du, Chenyue
A1  - Zhang, Yumei
A1  - Wang, Nan
A1  - Chong, Yunhao
A1  - Wang, Hongwei
A1  - Wu, Daohua
A1  - Liu, Jintao
A1  - Zhang, Hailong
A1  - Lu, Lingyun
A1  - Liu, Jiqiang
SP  - 244
EP  - 244
VL  - 9
IS  - 1
N2  - High-speed train operation data are reliable and rich resources in data-driven research. However, the data released by railway companies are poorly organized and not comprehensive enough to be applied directly and effectively. A public high-speed railway network dataset suitable for research is still lacking. To support the research in large-scale complex network, complex dynamic system and intelligent transportation, we develop a high-speed railway network dataset, containing the train operation data in different directions from October 8, 2019 to January 27, 2020, the train delay data of the railway stations, the junction stations data, and the mileage data of adjacent stations. In the dataset, weather, temperature, wind power and major holidays are considered as factors affecting train operation. Potential research values of the dataset include but are not limited to complex dynamic system pattern mining, community detection and discovery, and train delay analysis. Besides, the dataset can be used to solve various railway operation and management problems, such as passenger service network improvement, train real-time dispatching and intelligent driving assistance.<p />  <p>Language: en</p>
LA  - en
SN  - 2052-4463
UR  - http://dx.doi.org/10.1038/s41597-022-01349-8
ID  - ref1
ER  -