Air Traffic Forecast Empirical Research Based on the MCMC Method

Jian-bo Wang, Chong-jun Fan, Lei Bai

Abstract


Airport air traffic is one of the most important and hardest one among all the airport data forecasts. In this paper, the Markov Chain Monte Carlo (MCMC) method of applied theory of statistics has been introduced into the aviation sector, and the discussion on airport air traffic forecast has been conducted taking Shanghai airport as the application background. MCMC method is designed to solve the problem parameters expectations where some baysian inference can not be directly calculated. This paper conducts the iterative computation using WinBUGS, EViews is used to estimate the initial iteration parameter of the regression model, and it is on this basis that the regression equation under the MCMC method is obtained.


Full Text: PDF DOI: 10.5539/cis.v5n5p50

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Computer and Information Science   ISSN 1913-8989 (Print)   ISSN 1913-8997 (Online)
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