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cheliuliangyuce

于 2021-03-30 发布 文件大小:616KB
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  短时交通流预测是实现交通流诱导的关键技术之一。短时交通流因为其不确定性等特点而使其预测很复杂。本文通过实地调查获取的交通流量数据,分别采用移动平均法、指数平滑法、AR模型法三种交通流预测方法进行短时交通流量预测。(Traffic flow forecasting is one of the key technologies to achieve traffic induced. Traffic flow because the characteristics of its uncertainty and make it very complicated to predict. Traffic data presented herein obtained through field surveys were used moving average, exponential smoothing, AR model method in three short-term traffic flow forecasting method to predict traffic flow.)

文件列表:

客流量预测算法类比于交通量预测程序
..................................\Matlab_时间预测
..................................\...............\ardemo.asv,1175,2014-05-28
..................................\...............\ardemo.m,1179,2014-05-28
..................................\...............\armademo.m,1251,2014-04-27
..................................\...............\mademo.m,1442,2014-04-27
..................................\...............\mae.asv,84,2009-03-28
..................................\...............\mae.m,83,2009-03-25
..................................\...............\Main.m,1254,2009-03-22
..................................\...............\MSE.m,165,2009-03-22
..................................\...............\pic
..................................\...............\...\ar.bmp
..................................\...............\...\arma.bmp
..................................\...............\...\ma.bmp
..................................\...............\...\指数平滑.bmp
..................................\...............\...\非线性回归.bmp
..................................\...............\picnew





..................................\...............\regressdemo.asv,1136,2014-04-27
..................................\...............\regressdemo.m,1202,2014-04-27
..................................\...............\releaterror.asv,65,2009-03-28
..................................\...............\releaterror.m,162,2009-03-28
..................................\...............\smothdemo.asv,646,2009-03-22
..................................\...............\smothdemo.m,1185,2014-04-27
..................................\...............\时间序列数据.doc,26624,2009-03-18
..................................\...............\时间序列预测方法比较.pdf,152130,2009-03-15
..................................\...............\误差分析.xls,13824,2009-03-22
..................................\...............\误差分析_new.xls,13824,2009-03-23

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