Intelligence Computational Based Air Passenger Flow Distrbution In Uncertain Environment

For a long time, the research on the air travel market in mainland of China has taken aim only at a single market, for example, the passengers traffic at an airport, or an airline, or the whole country. There were a few researchs on the distribution of the passengers traffic among the areas of this country. After summarizing both internal and external literatures in field of air passenger transptation, this paper paid attention to the study on the distribution of the passengers traffic by mean of the theory analysis, empirical analysis and simulation. The four non-classical mathematical methods which contain the grey system theory, extenics, SPA analysis and fuzzy mathematics belong to intelligent computation method. The four non-classical mathematics are used as well as the traditional method of probability, regression techniques and gravity model in order to study the three kinds of air passenger flow distrbution in uncertain environment, those are distributions of air travel demand, passenger traffic at airports or nodes and air passenger OD flow.Firstly, the spatial analysis in air transptation relation was made in view of economic, social and geographical environment. A variety of factors were analysed, and the main factors were chosen by mean of the grey relation analysis. With the main factors, air travel demand generation in mainland of China are analysed based on extenics comprehensive evaluate method. The key factors of the 31 provincial areas are analysed too by mean of the SPA.Secondly, according to the principle that airport catchment areas give rise to the distributions of passenger traffic at nodes, the affecting factors are discussed, such as metropolitan area, airport and ground traffic to airport catchment areas. Three kinds of airport catchment areas model were put forward based on the distance, the demand and supply sides of air transportation and passengers'airport choice. The distance based airport catchment areas model was revised by using fuzzy membership function. The numerical experiments were made with the optimum planning model of airport service area. Disaggregated airport choice models in a multi-airport region were also established, with the case of Sunan Airport in Jiangsu province, empirical analysis was made.Thirdly, the affecting factors of OD passenger flows were discussed, so as the character of distance decay of this country's OD passenger flows. After comparing to the available distrubution model of OD passenger flows, the traditional standard gravity model was chosen, and this model was revised by adding 10 fictitious variables to it. For equal time interval, the inter-city airline passenger flows data on main flights in 1995, 2000, 2005 were used in order to calibrate the parameters of the 10 fictitious variables. The results of OD passenger flows distrubution are obtained by analyzing the values' change of the 10 fictitious variables. The 10 fictitious variables values from 2006 to 2010 were forecasted by GM(1,1) model, and get satisfactory results with empirical analysis by the partial inter-city airline passenger flows data on main flights in 2006.Finally, this paper analyzed the potential competition of the high-speed train with the air transport in future. Two kinds of airline distance model were established based on the equality in travel time and travel cost. The city-pair's combination split model between high-speed train and air transport was put forward. The fictitious reverse gravity model was also established based on the mechanism that the changing of air passenger OD traffic flows affected passenger traffic at airport causing by competition between the high-speed train and the air transport.