The DOI matches its Crossref record.
Real Time Estimation of Bus Arrival Time under Mobile Environment
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In the citing paper
“The server database [12] can be organized in many ways, to reduce memory requirement, improve access speed, or reduce the number of queries. To improve the query speed, the tables related to buses are partitioned into static and dynamic ones.”
From Implementation of a Real Time Passenger Information System (2012) · cites this paper as [12]
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 7
- Bae, D.: An analysis on the efficiency of bus information systems in Bucheon city. J. Korean Society for Transportation(JKST) 20, 7–18 (2002)
- Cathey, F.W., Dailey, D.J.: Transit vehicles as traffic probe sensors. In: TRB (2002) · DOI
- Chien, S., et al.: Dynamic bus arrival time prediction with artificial neural networks. J. of Transp. Eng. 128 (2002) · DOI
- Ko, S.: A study on bus arrival information for BIS. JKTS 20, 175–181 (2002)
- Mitchell, G.: Machine Learning. Mc-Grawhill, New York (1995)
- Park, B., et al.: Development of a neural-based model for forecasting link travel times. JKTS 13, 95–112 (1995)
- Quiroga, C.A., Bullock, D.: Travel time studies with global positioning and geographic information systems: an integrated methodology. Trans. Research 6C, 101–127 (1998) · DOI
Cited by
Implementation of a Real Time Passenger Information System
Ganesh, K., Thrivikraman, M., Kuri, J., Dagale, H., Sudhakar, G., & Sanyal, S. (2012) · arXiv · doi:10.48550/arxiv.1206.0447 · Cited by 35
Metadata
- Authors
- Park, T., Lee, S., & Moon, Y.-J.
- Affiliations
- Soongsil University (KR)
- Korea Research Institute for Human Settlements (KR)
- Korea Transport Institute (KR)
- ORCID
- Park, Taehyung
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2004
- Pages
- 1088-1096
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1513214281
- Cited by
- 21
- References
- 0
- Citations by year
- 2023: 2 · 2022: 1 · 2020: 1 · 2019: 1 · 2015: 1 · 2014: 1 · 2013: 1 · 2012: 2
- FWCI
- 5.31
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Social Sciences › Transportation › Transportation Planning and Optimization
- Social Sciences › Transportation › Traffic Prediction and Management Techniques
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Keywords
- bus arrival time estimation, bus information system, link travel time estimation, artificial neural networks, mobile environments, wireless communication, feedback control, real-time transit information, ITS
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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.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Real Time Estimation of Bus Arrival Time under Mobile Environment. https://app.cochat.ai/papers/10.1007/978-3-540-24707-4_122
- The paper
- Park, T., Lee, S., & Moon, Y.-J. (2004). Real Time Estimation of Bus Arrival Time under Mobile Environment. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-540-24707-4_122