基于交通数据挖掘的交通流预测模型构建  

Research on Traffic Flow Prediction Model Based on Traffic Data Mining

作　　者：李以诚 叶青[1] LI Yi-cheng;YE Qing(Changsha University of Science&Technology,Changsha 410000 China)

机构地区：[1]长沙理工大学,湖南长沙410000

出　　处：《自动化技术与应用》2021年第3期39-41,45,共4页Techniques of Automation and Applications

摘　　要：我国是一个汽车大国,在人均汽车保有量逐年增加的情况下,道路交通拥堵的问题越来越突出。新形势下的交通运输管理工作应当充分发挥数学模型的作用,将数学模型与计算机、互联网等硬件资源有机结合起来,有针对性地制定交通管理方案。因此,本文设计了一套基于交通数据挖掘的交通流预测模型,旨在提升交通流预测的准确性,优化流通管理工作路径。China is a big automobile country,with the increase of per capita car ownership year by year,the problem of road traffic congestion is becoming more and more prominent.The traffic and transportation management under the new situation should give full play to the role of mathematical model,combine the mathematical model with computer,Internet and other hardware resources organically,and formulate the traffic management scheme pertinently.Therefore,this paper designs a set of traffic flow prediction model based on traffic data mining,which aims to improve the accuracy of traffic flow prediction and optimize the working path of circulation management.

关 键 词：交通预测模型 GM模型 灰色系统理论 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]