AI-based Models for Resource Allocation and Resource Demand Forecasting Systems in Aviation: A Survey and Analytical Study

dc.contributor.authorHejji, Dina
dc.contributor.authorAbu Talib, Manar
dc.contributor.authorBou Nassif, Ali
dc.contributor.authorNasir, Qassim
dc.contributor.authorBouridane, Ahmed
dc.date.accessioned2022-06-03T06:21:25Z
dc.date.accessioned2023-08-19T08:18:52Z
dc.date.available2022-06-03T06:21:25Z
dc.date.available2023-08-19T08:18:52Z
dc.date.issued2021-11
dc.description.abstractThere is an increasing interest in developing Intelligent Decision Support Systems (IDSSs) for various aviation operations such as resource planning. Recently, with the significant advancements in Machine Learning (ML), it has been widely used to develop the core methods for IDSSs. Thus, researchers have broadly used ML to address Resource Allocation and Resource Demand Forecasting (RARDF) in aviation industry. This research paper reviews the resources that have been tackled by Artificial Intelligence (AI) based Intelligent Systems in aviation industry. In addition, it reviews the most recent ML-based work done in RARDF and analyzes the possibilities and challenges for this paradigm in aviation industry.en_US
dc.identifier.citationHejji, D., Talib, M. A., Nassif, A. B., Nasir, Q., & Bouridane, A. (2021, November). AI-based Models for Resource Allocation and Resource Demand Forecasting Systems in Aviation: A Survey and Analytical Study. In 2021 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) (pp. 183-189). IEEE.en_US
dc.identifier.doihttps://doi.org/10.1109/IoTaIS53735.2021.9628555
dc.identifier.urihttps://edms.wexl.in/handle/1/3620
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectMachine learningen_US
dc.subjectIntelligent Decision Support Systemsen_US
dc.subjectResource Allocationen_US
dc.subjectForecastingen_US
dc.titleAI-based Models for Resource Allocation and Resource Demand Forecasting Systems in Aviation: A Survey and Analytical Studyen_US
dc.title.alternativejournal Articalen_US
dc.typeArticleen_US

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