Using S-ANN Method to Forecast the Ridership of Beijing Public Transportation

Purely quantitative methods are in a dilemma situation to handle the real world problem, such as transportation and traffic problems, these quantitative methods are thus necessary to combine with the qualitative methods which are responsible to cope with our incomplete knowledge, because these incompletely qualitative knowledge are the important components of our knowledge structure. In this paper, S-ANN method is employed as a forecasting tool to forecast the ridership of Beijing public transportation from year 2001 to 2005 based on the last 20-years historically statistical data. For S-ANN, the artificial neural network (ANN) of AI is used to handle the quantitative knowledge and the SCENARIO method of Systems Engineering is used to handle the qualitative knowledge respectively. The forecasting results show that S-ANN is practical and easy to operate.