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交通量

与 交通量 相关的网络例句 [注:此内容来源于网络,仅供参考]

The traffic is very heavy, and has begun to block up the streets.

交通量很大,已经开始把街道阻塞住了。

But along with the highway traffic development, the volume of traffic increases, the axle load increases and the canalization and so on, set a higher request to the structure and performance of the road surface.

但是随着我国公路交通的发展、交通量增大、轴载增加、交通流的渠化等,对路面结构和材料性能提出了更高的要求。

A satisfactory design could only be gained by the choice of an appropriate channelizing mode according to the road characteristics, traffic volume and flowing etc.

这种交通组织简便、不需设置信号灯控制交通,但通行能力有限,一般适应的交通量以1800~2700辆/h为宜。

This model contains two parts,one is conceptive model and the other one is reasoning model.

设计的自动决策支持模型中包含了概念模型和推理模型,推理模型中集成了交通拥挤自动检测算法和拥挤交通量控制方案选择的模糊推理算法。

This model contains two parts, one is conceptive model and the other one is reasoning model. The fuzzy reasoning algorithm of traffic control and the automatic detection algorithm for traffic congestion are integrated in the reasoning model.

设计的自动决策支持模型中包含了概念模型和推理模型,推理模型中集成了交通拥挤自动检测算法和拥挤交通量控制方案选择的模糊推理算法。

For the limitations of traditional algorithms that can not be reasonably accurately predict the traffic, we have adopted BP neural network and curvilinear regression algorithms. First, we use BP neural network to train on historical data and then use the curve of regression to predict various factors, and then forecast data into the trained BP neural network which has been trained well, you can get future traffic forecasts.

针对以上传统算法的局限性,采用BP神经网络与曲线回归耦合算法,用BP神经网络对历史数据训练,利用曲线回归对各因素待测年份之值预测,将各因素的预测值带入已训练好的BP神经网络中,即可得到未来交通量的预测值。

Key words: traffic forecast; curvilinear regression; BP neural network; curvilinear regression coupling algorithm; traffic

引用格 式:范加冬,张令刚。BP,曲线回归耦合算法在交通量预测中的应用。中国科技论文在线精品论文,2010,3(6):619~622。

Similarly a physical count is normally used to establish the volume of traffic on key roads and the volume of different brands sold by important retail outlets (increasingly via electronic point of sale — EPOS — installations).

同样,实物清点通常是用来建立的交通量的主要道路和数量的不同品牌销售的重要的零售商店(越来越多地通过电子销售点-电子销售点-设施)。

Simulation results show that the two kinds of method could all solve the forecast problem to traffic flow effectively.

研究表明,这两类模型都能够有效地解决区域交通控制中交通量的预测问题。

If you do, then you will likely see a large increase in traffic to your own website.

如果你这样做,那么你很可能会看到一个大交通量的增加,以你自己的网站。

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