TY - JOUR A2 - Xin, Qin AU - Sun, Feng AU - Su, Wenheng AU - Liu, Weixuan AU - Cao, Hui AU - Guo, Dong AU - Zhu, Ye PY - 2018 DA - 2018/11/25 TI - Analysis of Bus Trip Characteristics and Demand Forecasting Based on NARX Neural Network Model SP - 2975615 VL - 2018 AB - In recent years, there has been increased interest in the use of bus IC card data to analyze bus transit time characteristics, and the prediction is no longer confined to rail traffic passenger flow prediction and traditional traffic flow prediction.客运总线IC卡预测研究逐年增加基于青岛市总线IC数据,本文首先分析子段客流特征并单独研究长者特征结果显示,老年人旅行也受到周日和周末的影响。依据ARIMA模型和NARX神经网络模型,客流预测(10分钟间隔)使用ICnc卡数据一总线5个工作日预测结果显示NARX神经网络模型对客运流短期预测有效,特别是峰值时和大规模数据预测更精确SN-2090-0147UR-https://doi.org/101155/2018/2975615DO-10.1155/2018/2975615JF-电气计算机工程杂志PB-HindawiKW-ER