Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022)

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Analysis Of Change Trend Based On K-means And Characteristics Of China’s Railway Operation

Authors
Wending Jin1, Jinyi Li2, Zhuohao Fang3, *
1Faculty of Science, Minzu University Of China, Beijing, China
2Institute of Artificial Intelligence, Southwest University, Chongqing, China
3Faculty of information technology, Macau University of Science and Technology University, Macau, China
*Corresponding author. Email: 19098533i011016@student.must.edu.mo
Corresponding Author
Zhuohao Fang
Available Online 29 December 2022.
DOI
10.2991/978-94-6463-042-8_64How to use a DOI?
Keywords
K-means; High-speed railway; The evolution trend; High-speed operation
Abstract

With the advantages of high speed and high efficiency, railway has rapidly become the core of the national transportation system. At the same time, railway industry is also developing vigorously. In this paper, the quantity data of intercity railways, high-speed railways and ordinary trains in 118 cities from 2008 to 2021 are selected as samples, and k-means clustering method is used to conduct clustering analysis and processing on railway train number data, and cities are divided into eight categories. Based on the analysis of specific national policies, the characteristics of each type of city and the quantitative characteristics of different types of trains in the annual clustering results are obtained, and the alluvial map is drawn according to the clustering results, and the transformation law between different types of cities and the number evolution trend of different types of trains are obtained. The results show that: Urban train operation is closely related to the level of administrative management, geographical location and economy of the city.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022)
Series
Advances in Computer Science Research
Publication Date
29 December 2022
ISBN
10.2991/978-94-6463-042-8_64
ISSN
2352-538X
DOI
10.2991/978-94-6463-042-8_64How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Wending Jin
AU  - Jinyi Li
AU  - Zhuohao Fang
PY  - 2022
DA  - 2022/12/29
TI  - Analysis Of Change Trend Based On K-means And Characteristics Of China’s Railway Operation
BT  - Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022)
PB  - Atlantis Press
SP  - 439
EP  - 447
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-042-8_64
DO  - 10.2991/978-94-6463-042-8_64
ID  - Jin2022
ER  -