Abstract

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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