Cited by 50Transportation Planning and OptimizationAviation Industry Analysis and TrendsRailway Systems and Energy Efficiency

Analyzing high speed rail passengers’ train choices based on new online booking data in China

Sun, Yanshuo, Jiang, Zhibin, Gu, Jinjing, Zhou, Min, Li, Yeming, Zhang, Lei·2018·Transportation Research Part C: Emerging Technologies

Integrity signals

Registry

Crossref · 10.1016/j.trc.2018.10.015

Cites

30 of 30 references verified0 citation errors · 0 not checkable

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Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Sun et al. use SVMs and neural networks for analyzing preferences of high-speed rail customers in China.

    “Sun et al. [770] use SVMs and neural networks for analyzing preferences of customers traveling by high speed rail in China.”

    From Tackling climate change with machine learning (2023) · cites this paper as [770]

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Authors
Sun, Y., Jiang, Z., Gu, J., Zhou, M., Li, Y., & Zhang, L.
Affiliations
  • Florida State University (US)
  • Tongji University (CN)
  • University of Maryland, College Park (US)
Corresponding author
Jiang, Zhibin
Venue
Transportation Research Part C: Emerging Technologies
Publisher
Elsevier BV
Published
2018-12
Volume
97
Pages
96-113
ISSN
0968-090X (ISSN-L)
OpenAlex
W2898530914
Cited by
50
References
29
Citations by year
2026: 6 · 2025: 5 · 2024: 5 · 2023: 11 · 2022: 7 · 2021: 8 · 2020: 5 · 2019: 3
FWCI
4.95
Type
journal article
Language
en
Open access
closed
Locations
Transportation Research Part C Emerging Technologies (publishedVersion)
Funders
  • National Natural Science Foundation of China (61473210)
  • Fundamental Research Funds for the Central Universities
  • China Railway Corporation (2016X005-G)
Topics
  • Social Sciences › Transportation › Transportation Planning and Optimization
  • Social Sciences › Economics, Econometrics and Finance › General Economics, Econometrics and Finance › Aviation Industry Analysis and Trends
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Railway Systems and Energy Efficiency
Keywords
high-speed rail, support vector regression, artificial neural networks, load factor

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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