Dynamic Traffic Demand Forecasting Based on Microzone: A Spatial Analysis of Smart Card Data Using Machine Learning Methodologies.
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| Title: | Dynamic Traffic Demand Forecasting Based on Microzone: A Spatial Analysis of Smart Card Data Using Machine Learning Methodologies. |
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| Authors: | Kim, Kyoungtae1 (AUTHOR), Lee, Inmook2 (AUTHOR), Choi, Solsaem2 (AUTHOR), Song, Ki-Han2 (AUTHOR) kihansong@seoultech.ac.kr, Habib, Mohammad Rezwan (AUTHOR) mohabib@wiley.com |
| Source: | Journal of Advanced Transportation. 6/23/2026, Vol. 2026, p1-18. 18p. |
| Database: | Academic Search Ultimate |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: asn DbLabel: Academic Search Ultimate An: 194783682 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1155/atr/5849967 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 1 Titles: – TitleFull: Dynamic Traffic Demand Forecasting Based on Microzone: A Spatial Analysis of Smart Card Data Using Machine Learning Methodologies. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kim, Kyoungtae – PersonEntity: Name: NameFull: Lee, Inmook – PersonEntity: Name: NameFull: Choi, Solsaem – PersonEntity: Name: NameFull: Song, Ki-Han – PersonEntity: Name: NameFull: Habib, Mohammad Rezwan IsPartOfRelationships: – BibEntity: Dates: – D: 23 M: 06 Text: 6/23/2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 01976729 Numbering: – Type: volume Value: 2026 Titles: – TitleFull: Journal of Advanced Transportation Type: main |
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