City Taxi "Supply to Match" Degree Analysis and Solution Algorithm

In this paper, we focus on the need to solve the problem through reasonable index, based on a taxi drops quickly intelligent software platform, with Beijing as an example, Analysis the degree of “The matching of supply and demand” under different time and space. This paper has established three kinds of methods, they are analysis method, no-load ratio method and get the data through Python program [1]. And we also used MATLAB R2014b, Python, SPSS software, etc. Based on taxi no-load ratio as the major factors in control measure "the matching of supply and demand". By using principal component analysis to select reasonable factors that influences the matching of supply and demand. Get the internal relationships between the variables by SPSS software, and finally we selected taxi's distribution of quantity and demand as reasonable index. Drawing three-dimensional image with time and space as independent variables, impact index as the dependent variable through MATLAB, we use it to express no-load ratio and then reflect the degree of “The matching of supply and demand ” under different time and space. To Get the Data First, model data is based on drops quick smart travel platform, platform data update in real time, so the data cached in the local, then we using python language to get the intelligent platform of data for parsing and processing. The data for each index in the platform is presented in an hour. In this paper, the city of Beijing is divided according to the rectangular ring in ideal, with latitude and longitude as the limiting condition, get every hour and every lot of taxi demand, taxi distribution and taxi costs that three indicators. Because data is obtained from the intelligent platform in real time, so the value displayed by the program will be changed according to the update of the website data.