基于人工智能的航空资源配置与需求预测系统模型:调查与分析研究

D. Hejji, M. A. Talib, A. B. Nassif, Q. Nasir, A. Bouridane
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引用次数: 2

摘要

为各种航空业务(如资源规划)开发智能决策支持系统(idss)的兴趣日益增加。近年来,随着机器学习(ML)的显著进步,机器学习已被广泛用于开发idss的核心方法。因此,研究人员广泛使用机器学习来解决航空工业中的资源分配和资源需求预测(RARDF)问题。本文综述了基于人工智能(AI)的航空工业智能系统已经解决的资源。此外,它还回顾了RARDF中最近完成的基于ml的工作,并分析了该范式在航空业中的可能性和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI-based Models for Resource Allocation and Resource Demand Forecasting Systems in Aviation: A Survey and Analytical Study
There 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.
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