山东建筑大学学报Issue(3)：205-210,6.
基于BP神经网络的公交周转时间预测研究
Bus turnaround time prediction research based on the BP neural network
摘要
Abstract
Bus turnaround time is the key parameter of bus driving operation plan,and the accurate prediction of the bus turnaround time is also important guarantee to improve the service level of public transportation.Based on the bus running dynamic randomness and by using the ordered sample clustering data mining algorithm,the paper analyzes the distribution features of the bus turnaround time in each time window to get the main dynamic factors,establishes the bus turnaround time prediction model,and through example analysis verifies the effectiveness and accuracy of the model. The results show using GPS data can obtain the accurate bus running bus turnaround time,and by partitioning time window,the bus turnaround time approximately normally distributed at the same time window.Through the establishment of the BP neural network prediction model can effectively reveal the bus turnaround time and the nonlinear relationship between the dynamic factors,and the example analysis results show that the forecasting bus turnaround time mean absolute percentage error is 5.69%,which has higher prediction accuracy.关键词
公交周转时间/时间窗/分布特征/动态因素/BP 神经网络Key words
bus turnaround time/onfluencing factors/distribution characteristics/time window/BP neural network分类
交通工程引用本文复制引用
史同广,袁腾飞,时柏营..基于BP神经网络的公交周转时间预测研究[J].山东建筑大学学报,2015,(3):205-210,6.基金项目
国家“十二五”科技支撑计划项目 （）
