Research Overview of Civil Aviation Passenger Traffic Forecasting Methods
In order to improve the operating efficiency of civil aviation,accurately predict passenger traffic and promote the sustainable development of civil aviation,a taxonomy is used to classify civil aviation passenger traffic forecasting methods into traditional statistical methods,machine learning and combination models.The improvement principle,effect and application of each method are introduced in detail,the precision is improved by data processing,weight adjustment,parameter optimisation and structure improvement,and the advantages of combinatorial model over single model are summarized.Empirical results show that prediction model have higher accuracy than single models,and it is pointed out that combining the development trend of artificial intelligence and big data technology,constructing excellent combinatorial prediction models is a potential research direction to improve prediction accuracy.
civil aviation passenger traffictime series forecastingmachine learningneural networkcombined forecasting
NETL
NSTL
万方数据
