一种基于改进频繁树模型的智能交通信息关联挖掘方案  

An Intelligent Transportation Information Association Mining Scheme Based on Improved Frequent Tree Model

作　　者：黄宇达[1] 王超杰[1] 赵红专[2] 王迤冉[3] 

机构地区：[1]周口职业技术学院信息工程系,周口466000 [2]重庆大学自动化学院,重庆400044 [3]周口师范学院计算机科学与技术学院,周口466000

出　　处：《计算机与数字工程》2015年第2期210-214,共5页Computer & Digital Engineering

基　　金：重庆市科技攻关计划项目(编号:CSTC2012gg-yyjsB30001);河南省基础与前沿技术研究计划项目(编号:122300410397)资助

摘　　要：针对传统交通系统在对海量交通信息深层次处理和分析上的不足,文章提出了一种新的智能交通系统体系结构以及一种基于该结构和数据挖掘技术的改进频繁树模型的关联挖掘分析方案。该方案运用系统工程的思想,对改进算法的步骤及其关键技术的实现做了详细阐述,最后通过实验对比验证了该方案的可行性及有效性。实验结果表明:该方案不仅能够实现对智能交通信息快速而有效的挖掘,而且还能根据需求得到精确、简练的有用信息,为评估和决策提供准确依据。For the lack of the traditional traffic system in in‐depth processing and analyzing for the massive traffic infor‐mation ,the paper presents a new architecture of ITS ,and a association mining analysis program of improved frequent tree model based on the architecture and data mining technology .The scheme uses the thought of system engineering ,elaborates the improved algorithm steps and key technologies ,finally the experiment verifies the feasibility and effectiveness of the scheme .Experimental results show that the scheme not only can realize quickly and effectively mining the intelligent traffic information ,according to requirement ,but also obtain accurate ,concise and useful information ,to provide accurate data for the evaluation and decision making .

关 键 词：数据挖掘 智能交通系统 交通信息 关联规则 频繁树模型 系统工程 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]