摘要
大众出行需求增高,传统的城市交通已不能满足人们出行的各种需求,在数据挖掘技术快速发展的背景下,智慧交通应运而生。作为智慧交通的一种典型应用,交通拥堵预测越来越受大众的青睐。探讨数据挖掘技术在智慧交通道路拥堵预测案例中的应用,分别从数据采集、数据清洗和预处理、模型构建与应用等方面进行说明。
With the increase of people's travel demand,traditional urban transportation can't meet people's travel needs.Under the background of the rapid development data mining technology,intelligent transportation came into being.As a typical application of intelligent transportation,traffic congestion prediction is increasingly favored by the public.This paper discusses the application of data mining technology in intelligent traffic road congestion prediction,and explains it from the aspects of data acquisition,data cleaning and preprocessing,and model construction and application.
作者
张群慧
彭辉
刘军华
ZHANG Qun-hui;PENG Hui;LIU Jun-hua(Hunan Vocational College of Science and Technology,Changsha,Hunan,China 410004;Hunan Post and Telecommunication College,Changsha,Hunan,China 410015)
出处
《湖南邮电职业技术学院学报》
2022年第3期36-39,共4页
Journal of Hunan Post and Telecommunication College
基金
2019年湖南省社会科学成果评审委员会课题“大数据时代智慧交通应用与发展策略研究”(课题编号:XSP19YBC189)。
关键词
智慧交通
数据挖掘
聚类分析
拥堵预测
intelligent transportation
data mining
cluster analysis
congestion prediction