华中科技大学学报（自然科学版）2016，Vol.44Issue(8)：36-40,5.DOI:10.13245/j.hust.160808
基于数据挖掘的高速公路行程时间预测
Freeway travel time prediction based on clustering method with data mining
摘要
Abstract
Model chooses freeway history data was set as the research object to predict freeway travel time .Historical data of traffic travel time was categorized into different sample types using cluster a‐nalysis .Traffic data of travel time was classified and identified by actual characteristics of historical data .Freeway travel time prediction model was structured using data mining .The instance data was the real data recorded from toll stations of Shandong province .Analysis used the instance data fore‐cast model and calculated the mean absolute percentage error of algorithm .To illustrate the validity of the mode ,actual test set was applied to a variety of algorithms of travel time prediction .The compari‐son between the prediction errors of the algorithms was given .The results show that the modified k‐means algorithm mentioned in the paper improves the accuracy of prediction .Model decreases the cost of data acquisition ,and provides reliable prediction of travel time for the information service .The model provides powerful decision basis for travelers .关键词
高速公路/行程时间预测/预测强度/数据挖掘/k-means法/联网收费数据Key words
freeway/travel time prediction/predict strength/data mining/k-means method/networ-king toll data分类
交通工程引用本文复制引用
邢雪,于德新,田秀娟,程泽阳..基于数据挖掘的高速公路行程时间预测[J].华中科技大学学报（自然科学版）,2016,44(8):36-40,5.基金项目
国家自然科学基金资助项目（51308249）；山东省省管企业科技创新项目（20122150251-1）． （）
