小世界模型为研究城市道路网络的拓扑结构和内在特征等提供了新的视角和方法。
Small world model provides a new aspect and method for exploring the topological structure and intrinsic characters of urban road network.
建立城市道路交通安全评价体系，运用MATLAB软件进行编程，实现模型的运算，并得到评价结果。
Establish the evaluation system of urban road traffic safety. Finally, computing implementation model and obtaining the evaluation results with MATLAB software programming.
将灰色物元评价方法应用于城市道路交叉系统评价，分析了城市道路交叉系统的影响因素，建立了城市道路交叉系统评价的灰色物元评价模型。
By applying the grey matter-element evaluation method to the city road cross system, this paper analyses the influence factors of the system and constructs its grey matter-element evaluation model.
本文提出了基于交通效率的城市道路网络的双向优化模型。
This paper puts forward a bi-level optimization model of urban road network based on transport efficiency.
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。
Accordingly, this paper proposes a fusion-prediction model of traffic-flow in urban road-intersection based on integrated ANN (Artificial Neural Network).
本研究在地理信息系统集成了交通噪声预测模型的基础上，设计和开发了基于地理信息系统的城市道路交通噪声预测系统。
The research integrates the prediction of traffic noise into the geography information system, and designs and develops the urban road traffic noise prediction system which is based on the GIS.
小世界模型为研究城市道路网络的拓扑结构和内在特征等提供了新的视角和方法。
The objectives of city road network planning and shortcomings of the available programming models were analyzed.
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。
The improved CA model can be used for simulating the urban road traffic flow of median speed.
提出基于城市道路网络容量约束下的交通目标结构优化模型，分析了模型的意义。
According to the city road network capacity restriction, Put forward the optimization model of the traffic target structure, and analyze the meaning of the model.
针对影响城市道路安全状况的因素众多且具有模糊性的特点，采用模糊模式识别与模糊综合评价相结合的评价模型来评价城市道路安全状况。
Considering the various and vague factors influencing urban road safety, the evaluation model used in the paper is combined by fuzzy pattern recognition and fuzzy comprehensive evaluation models.
通过对其需求量影响因素进行分析，建立了城市道路信息管网需求量的预测步骤及模型。
This paper analyzes the influencing factors of information culvert network demand and establishes prediction steps and prediction 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。
It includes urban road traffic net structure model, traffic flow generation model, vehicle run behavior model, and urban road traffic net analysis model.
由于城市道路交通问题具有不确定性和不精确性，故采用基于粗糙集的交通信息提取计算理论建立城市道路行程时间预测模型。
Since urban travel times are stochastic and uncertain, a model for addressing urban travel time prediction by using transport information granular computing theory based on rough set was proposed.
最后，通过柳州市城市道路交通安全的实例分析，证明对于所建立的评价体系和模型的研究具有较强的实用价值。
At last, the practically value of the study of the founded evaluation system and the evaluation model were proved by the example of Liuzhou urban road safety.
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。
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.
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。
The results show that the GRNN model constructed in this way can precisely forecast urban short-term traffic flow.
最后，在详细讨论路段能力使用系数、路段能力可靠性和备用能力相互关系之上，论文建立了基于能力可靠性的城市道路交通离散网络设计模型。
The computed results testify that it is feasible to apply Chaotic Algorithm to solve the bilevel programming problem and the solutions of model are correspondence with the reality traffic situations.
最后，在详细讨论路段能力使用系数、路段能力可靠性和备用能力相互关系之上，论文建立了基于能力可靠性的城市道路交通离散网络设计模型。
The computed results testify that it is feasible to apply Chaotic Algorithm to solve the bilevel programming problem and the solutions of model are correspondence with the reality traffic situations.
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