Abstract
The Hong Kong Flight Information Region (HKFIR) is surrounded by the airspaces of Guangzhou, Sanya, Taipei and Manila. International/regional flight routes to and from the Hong Kong International Airport (HKIA) rank among the busiest in the world. Air traffic flow rate is a complex parameter influenced by a variety of factors such as weather, business operation and regulations, etc. Accurate prediction of flow rate allows airport management to optimise tactical planning and decision making, potentially benefitting airport operations and air traffic efficiency. Leveraging the concept of Big Data, this paper establishes a preliminary algorithm for artificial intelligence prediction of air traffic flow rate at HKIA through supervised machine learning. Results based on 2017 data showed positive short-term prediction skills as well as superior performance over persistence based on the previous day.
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