Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/113969
DC FieldValueLanguage
dc.contributorMolecular Diversity Preservation International (MDPI)-
dc.creatorLiu, H-
dc.creatorLi, S-
dc.creatorSun, F-
dc.creatorFan, W-
dc.creatorIp, WH-
dc.creatorYung, KL-
dc.date.accessioned2025-07-04T08:35:01Z-
dc.date.available2025-07-04T08:35:01Z-
dc.identifier.issnAerospace-
dc.identifier.urihttp://hdl.handle.net/10397/113969-
dc.language.isoenen_US
dc.publisherAerospaceen_US
dc.rightsCopyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Liu, H., Li, S., Sun, F., Fan, W., Ip, W.-H., & Yung, K.-L. (2024). Adaptive Dynamic Programming with Reinforcement Learning on Optimization of Flight Departure Scheduling. Aerospace, 11(9), 754 is available at https://doi.org/10.3390/aerospace11090754.en_US
dc.subjectDepartment of Industrial and Systems Engineeringen_US
dc.titleAdaptive dynamic programming with reinforcement learning on optimization of flight departure schedulingen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume11-
dc.identifier.issue9-
dc.identifier.doi10.3390/aerospace11090754-
dcterms.abstract10.3390/aerospace11090754-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAerospace, Sept 2024, v. 11, no. 9, 754-
dcterms.issued2024-09-
dc.identifier.scopus2-s2.0-85205100225-
dc.identifier.eissn2226-4310-
dc.identifier.artn754-
dc.description.validate202507 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera3820-n06en_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China (52272356)en_US
dc.description.fundingTextKey Laboratory of Air Traffic Management System and Technology (SKLATM202001)en_US
dc.description.fundingTextCivil Aviation Safety Capability Building Project (ASSA2023/29)en_US
dc.description.fundingTextProject of Hong Kong Polytechnic University (WZOW)en_US
dc.description.fundingTextThe Research Centre of Deep Space Explorations (RCDSE), The Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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