County urban motor vehicle ownership prediction method based on support vector machine

Abstract

The invention discloses a county city motor vehicle ownership prediction method based on a support vector machine. The method comprises the following steps: examining the basic features and planning requirements of county cities and towns, constructing a motor vehicle ownership influence factor table, collecting the historical data, and building a data set; constructing a county town motor vehicleownership prediction model based on a support vector machine through model structure and parameter definition, model dimension and kernel function selection, factor initial value determination, modelconstruction and optimal solution; the obtained model is applied to verification set data for prediction, a prediction result and actual data are subjected to fitting analysis, and the accuracy and stability of the prediction model are verified according to precision requirements; if not, reconstructing the model; and if the requirements are met, predicting and planning the annual county urban motor vehicle ownership by utilizing the model. According to the invention, a county city and town carbon control and demand coupled traffic facility configuration system can be constructed, and low-carbon development of traffic planning is realized.

Description

technical field [0001] The invention belongs to the field of low-carbon traffic planning and automobile data prediction, and in particular relates to a method for predicting motor vehicle ownership in counties and towns based on support vector machines. Background technique [0002] Economic and social development has promoted the growth of motor vehicle ownership, which not only brings convenience to production and life, but also causes urban traffic congestion and environmental pollution. Studies have shown that the increase in the number of motor vehicles has basically a positive aggravating effect on the air quality in various places, especially the increasing carbon dioxide gas emissions continue to promote the deterioration of the atmospheric environment. In county towns and rural areas, with the development of urbanization, the continuous growth of residents' income has increased the penetration rate of motor vehicles; in order to avoid the problem of high carbon emis...

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Problems solved by technology

[0006] Purpose of the invention: Aiming at the problems of lack of comprehensiveness, applicability and accuracy in predicting the number of motor vehicles existing in the existing research, the present invention provides a historical analysis of the number of motor vehicles in counties and towns and its influencing factors by using the support vector machine algorithm. The method of learning from the data and then predicting the planned annual motor vehicle population

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