计算机应用 ›› 2018, Vol. 38 ›› Issue (4): 923-927.DOI: 10.11772/j.issn.1001-9081.2017092339
• 人工智能 • 下一篇
收稿日期:
2017-09-28
修回日期:
2017-12-04
出版日期:
2018-04-10
发布日期:
2018-04-09
通讯作者:
李盼乐
作者简介:
商建东(1968-),男,河南郑州人,教授,博士,主要研究方向:数据挖掘、高性能计算;李盼乐(1992-),男,河南洛阳人,硕士研究生,主要研究方向:轨迹挖掘;刘润杰(1972-),男,河南安阳人,副教授,博士,主要研究方向:通信网络特性、混沌分形方法;李润川(1991-),男,河南商丘人,博士研究生,主要研究方向:智慧医疗、机器学习。
SHANG Jiandong1, LI Panle1, LIU Runjie1, LI Runchuan2,3
Received:
2017-09-28
Revised:
2017-12-04
Online:
2018-04-10
Published:
2018-04-09
摘要: 针对出租车空载率高、司机寻客难的问题,提出泊松-卡尔曼组合预测模型(PKCPM)。首先,采用加权非齐次泊松模型,针对出租车历史数据进行建模,得到目标时刻的估计值;其次,基于当天的实时数据,将临近时刻乘客需求的平均值作为目标时刻预测值;最后,将预测值和估计值作为卡尔曼滤波模型的输入参数,实现对目标时刻出租车乘客需求的预测,同时引入误差反向传播机制,减小下一次预测误差。基于郑州市出租车轨迹数据集,对组合模型与非齐次泊松模型(NHPM)、加权非齐次泊松模型(WNHPM)、支持向量机(SVM)等三种模型进行对比,实验结果显示PKCPM的误差比WNHPM、SVM分别降低了8.85个百分点、14.9个百分点。该模型能对不同时段内、不同空间网格的乘客需求进行预测,为出租车寻找乘客提供可靠的依据。
中图分类号:
商建东, 李盼乐, 刘润杰, 李润川. 基于加权时变泊松模型的出租车载客点推荐模型[J]. 计算机应用, 2018, 38(4): 923-927.
SHANG Jiandong, LI Panle, LIU Runjie, LI Runchuan. Recommendation model of taxi passenger-finding locations based on weighted non-homogeneous Poisson model[J]. Journal of Computer Applications, 2018, 38(4): 923-927.
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