Research On Forecasting Method For Regional Airline Passenger Flow

With increasingly fierce market competition ,Domestic airlines begin to pay more attention to Revenue Management theories which play a crucial role in foreign airline companies.Accurate forecast of airline passenger flow is crucial for the development of regional airlines planning. There are many factors affect airline passenger flow, most important of them are price,available capacity,ATC and airport capacity. Because of the imbalance of supply and demand, it is very complex to forecast the regional airline passenger flow. Forecasting methods based on traditional statistics can not solve this problem properly. According to this, the thesis does some research on support Revenue Management based forecasting method for airline passenger flow.First of all, the characteristics of Regional airline passenger market and marketing strategies are described, and then the basic factors which affect airline passenger flow are analyzed.Secondly, the basic ideas and drawbacks of the airline passenger flow forecasting methods in common use such as Time Series Method;Regression Analysis Method and Neural Network Method etc. are introduced.Thirdly, an airline passenger flow forecasting model,which combining Time Series Method based model and Neural Network Method based model,is established based on Combination Forecast theory.Fourthly, an example is given to verify the validity of the Combination Forecast method based model for airline passenger flow.Finally,this thesis summarizes current study and proposes future research directions of airline passenger flow forecasting.