Parking Demand Prediction Of Xiamen Based On Interval Uncertainty

The parking demand forecasting is the foundation of the parking planning. However, uncertainty of demand is usually ignored in the traditional forecasting methods of parking demand, which easily bring decision risks. Xiamen city was selected as the research object in this thesis, uncertainty of demand was taken into full account, and the parking demand was forecasted, it has significant values in practice.At first, the current parking situation of the Xiamen city was investigated, and the parking demand characteristics and the parking facilities supply were analyzed, many urgent issues in parking facility planning were clear. The influencing factors of the parking demand in the Xiamen city was analyzed in this thesis, and the existing parking demand forecasting models were summarized, according to their shortcomings of ignoring uncertainty, the solution was proposed. It carrys on the theory of interval analysis, and analyze the advantages of the methods of using interval number to measure uncertainty of demand. On this basis, the parking demand forecasting model based on interval linear regression and the interval combination forecasting model were established separately, the result of interval prediction of Xiamen city was worked out. According to the existing urban planning level, the nonlinear regression model was established, and the interval supply structure of parking facilities of Xiamen city was worked out.The uncertainty of demand in parking demand forecasting was fully considered in this thesis, prediction results show that forecasting methods were reliable and effective, it has a good application prospect for urban parking planning in our country.