In this paper, an analytic and predicting model for urban region traffic flow status is presented by using several data mining technologies.
本文运用计算机科学领域中的数据挖掘技术，提出了一个城市区域交通流分析预测模型。
Practical prediction research of urban traffic flow shows that this model has famous predicted precision, and it can provide exact reference for urban traffic programming and control.
实际的城市交通流量预测研究表明，该模型具有较高的预测精度，可以为城市交通规划和控制提供准确的参考。
In order to solve serious urban transport problems, according to the proved chaotic characteristic of traffic flow, a non linear chaotic model to analyze the time series of traffic flow is proposed.
为了解决日益严重的城市交通问题，本文根据交通流已被证明的混沌特性，尝试采用非线性混沌模型来分析交通流时间序列。
Accordingly, this paper proposes a fusion-prediction model of traffic-flow in urban road-intersection based on integrated ANN (Artificial Neural Network).
基于此，本文提出了基于集成神经网络的城市道路交通流量的融合预测模型。
As far as content of studies, seven aspects are included: regional, central-place, urban hierarchical, commodity flow, interactive, diffusive, and model simulating linkages.
就研究内容而言，包括：地区联系、中心地联系、城市等级联系、商品流联系、相互作用联系、扩散联系、模型模拟间接反映的区域联系等七个方面；
The improved CA model can be used for simulating the urban road traffic flow of median speed.
改进后的CA模型，适用于对城市道路上中速车流运行状况的模拟。
It includes urban road traffic net structure model, traffic flow generation model, vehicle run behavior model, and urban road traffic net analysis model.
该体系结构由城市道路交通网络结构模型、交通生成模型、车辆行驶行为模型、城市道路交通网络分析模型四类模型组成。
The results show that the GRNN model constructed in this way can precisely forecast urban short-term traffic flow.
研究结果表明，构建的神经网络模型能够很精确地实时预测城市道路短期交通流。
Through analyzing the distribution of car flow in urban road, vehicle models of car, bus and heavy vehicle are set up separately. Based on the state of jam, vehicle loading model is established.
通过分析城市道路的车流分布特点，分别建立了小轿车、大型客车和重型车三类车辆模型，然后依据拥堵情况拟定针对城市桥梁拥堵的车辆荷载模型。
This paper presents a better method to determine node-flow in hydraulic model of urban water supply network.
为解决供水管网实时水力模型节点流量计算不准确的问题，提出了一种计算节点流量的方法。
The model can pre dict the air flow over and around the urban complex with reasonable success in a variety of synoptic situations.
此模式可在多种天气形势下相当成功地预报城市综合体上空及其周围的气流运动。
The model can pre dict the air flow over and around the urban complex with reasonable success in a variety of synoptic situations.
此模式可在多种天气形势下相当成功地预报城市综合体上空及其周围的气流运动。
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