Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/81398
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Khan, WA | en_US |
| dc.creator | Chung, SH | en_US |
| dc.creator | Ma, HL | en_US |
| dc.date.accessioned | 2019-09-24T00:53:20Z | - |
| dc.date.available | 2019-09-24T00:53:20Z | - |
| dc.identifier.uri | http://hdl.handle.net/10397/81398 | - |
| dc.description | Transportation Science and Logistics Conference 2020 (TSL 2020), Washington DC, USA, 27-29 May 2020 (cancelled) | en_US |
| dc.description.sponsorship | Department of Industrial and Systems Engineering | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | INFORMS | en_US |
| dc.rights | Posted with permission. | en_US |
| dc.title | Controlling air traffic congestion by predicting flight departure delays and duration : integrating machine learning sampling techniques and deep learning approaches | en_US |
| dc.type | Conference Paper | en_US |
| dc.identifier.spage | 1 | en_US |
| dc.identifier.epage | 5 | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Proceedings of the TSL Second Triennial Conference, 2020, 128, p.1-5. | en_US |
| dcterms.issued | 2020 | - |
| dc.relation.conference | Transportation Science and Logistics Conference (TSL) | en_US |
| dc.identifier.artn | 128 | en_US |
| dc.description.validate | 202006 bcma | en_US |
| dc.description.oa | Other Version | en_US |
| dc.identifier.FolderNumber | a0436-n01 | en_US |
| dc.description.pubStatus | null | en_US |
| Appears in Collections: | Conference Paper | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Khan_Controlling_air_traffic.pdf | 203.22 kB | Adobe PDF | View/Open |
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