| 短时交通流预测方法比较 |
| |
| 引用本文： | 唐丽娜,张卫华.短时交通流预测方法比较[J].交通科技与经济,2008,10(2):100-102. |
| |
| 作者姓名： | 唐丽娜 张卫华 |
| |
| 作者单位： | 合肥工业大学,交通研究所,安徽,合肥,230009 |
| |
| 摘 要： | 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。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3种交通流预测方法进行短时交通流量预测，并通过不同的评价指标对上述3种方法的预测效果进行评价，得出AR模型方法的预测效果优于其他2种方法。
|
| 关 键 词： | 智能交通系统 短时交通流预测 移动平均法 指数平滑法 AR模型法 |
| 文章编号： | 1008-5696(2008)02-0100-03 |
| 修稿时间： | 2007年11月19 |
The Discussion of Methods of Short-term Traffic Flow Forecast |
| |
| TANG Li-na,ZHANG Wei-hua.The Discussion of Methods of Short-term Traffic Flow Forecast[J].Technology & Economy in Areas of Communications,2008,10(2):100-102. |
| |
| Authors: | TANG Li-na ZHANG Wei-hua |
| |
| Institution: | (Research Institution of Traffic Engineering, HeFei University of Technology, HeFei 230009 ,China) |
| |
| Abstract: | Short-term traffic flow is one of the core technology to realize traffic flow guidance.It is complicated to forecast the traffic flow because of its uncertainty.Through the data obtained by fieldwork,the paper forecasts the short-term traffic by three methods:moving-average method,index-smoothing method,AR model method.Finally,we evaluate the three effects of the three methods through different evaluate targets and get the result that AR model is the better method. |
| |
| Keywords: | intelligent traffic system short-term traffic flow moving-average method index-smoothing method AR model method |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
