An Accurate Prediction Method for Airport Operational Situation Based on Hidden Markov Model

This paper is mainly devoted to an prediction method for airport operational situation which is one of the most important parts of the airport operation system. In order to provide theoretical support for high-level airport management, field operation management, air traffic control and airlines, and improve the service capacity of the airport, this paper makes a prediction study of the airport operation situation. Hidden Markov (HMM) prediction model is established based on the analysis of airport operation system. Baum-Welch and Viterbi algorithms are used to solve the prediction results. The model is validated and applied in a domestic hub airport. The results show that the prediction accuracy of HMM is 60 and 20% higher than that of Autoregressive Moving Average Model and Grey Markov model, respectively. It can also improve the situation value of airport operation situation, i.e. airport service capability. This method is more suitable for the analysis of airport operation.