基于支持向量機(jī)的時(shí)空二維融合正常與異常狀態(tài)的流量預(yù)測(cè).pdf

1、河北工業(yè)大學(xué)碩士學(xué)位論文基于支持向量機(jī)的時(shí)空二維融合正常與異常狀態(tài)的流量預(yù)測(cè)姓名：劉思明申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：道路與鐵道工程指導(dǎo)教師：李巧茹2010-12論文題目 II TRAFFIC FLOW IN NORMAL AND ABNORMAL PREDICTION USING TIME-SPACE FUSION MODEL BASED ON SUPPORT VECTOR MACHINES ABSTRACT With the high

2、-speed development of the national economy and the urbanization, urban transport development has been rapid progress. However, improvement of living standards of urban residents, the rapid growth of vehicle ownership, l

3、eading to between surge in road traffic and the limited road resources continue to intensify the contradiction causing a series of traffic problems, such as the more serious traffic congestion, traffic accidents and th

4、e environment pollution and so on. The development of domestic and international experience has shown over the years, any country or region can solve traffic congestion problems by large-scale road construction. Under

5、 current conditions, only the rational use and maximize exert the potential of urban road network, can be integrated and coordinated balance between vehicles and roads. The solution to this problem is to correctly eval

6、uate the basis of the current work status of urban road network, as defined by quantitative analysis of the reliability of calculations to evaluate the level of traffic. As one of the basic indicators of traffic engine

7、ering, traffic volume predict can not be ignored. Traffic predict for the current study generally ignored the interdependence at the same time between different sections. From the perspective of the entire road network,

8、 congestion or failure of the upstream and downstream sections, the section associated with will be affected. Therefore, reliability analysis which considered the relationship between sections is necessary. This paper

9、 presents a support vector machine (SVM) fusion of concurrent two-dimensional space-time predict method of traffic flow in two parallel system model to reduce the time cost. Also considered the relevance between time a

10、nd space, on two-dimensional space-time fusion, greatly improving the predict accuracy. It can be effectively evaluate the reliability of travel time to provide more accurate data to support. This paper analyzes the in

11、ternational issues of common urban transport firstly, and make a general description of the basic principles and requirements for the effective way of evaluation of transportation system currently--- network reliability

12、 analysis. As the reliability analysis of network traffic requires a lot of projections, which leads to the contents of this research - the state of normal and abnormal traffic flow predict. By researches the basic the

13、ory of SVM research and development, and selects the methods based on support vector machine regression model to predict the traffic flow under normal and abnormal in space-time two-dimensional fusion model, and compa

14、res with the results of multiple regression method under normal and abnormal state, you can visually see the two-dimensional fusion model based on support vector machine shows better performance. KEY WORDS： support vec