交通均衡模型体系是按照用户均衡原则描述网络交通流的模型集合。
Equilibrium traffic model is a set of models in which network traffic flow is described by user's equilibrium principle.
交叉口是道路网络的基本节点，也往往是网络交通流运行的瓶颈口。
The crossroad is the basic point of the urban roads, it may be the neck of the traffic flow operation.
本论文是结合国家自然科学基金资助项目“模拟电路系统网络交通流特性研究”完成的。
This paper was integrated with the project " The research of the traffic network flow characteristics by simulating circuit system" imbursed by National Natural Science Foundation of China (NSFC).
城市路网交通流是一种网络交通流，它是一个复杂的，具有开放性、自适应性和具有突变特征的系统。
The traffic flow of urban transportation network is a network flow, it a complex openness adaptivity mutation system.
城市交通模型从系统角度研究了网络交通流的相变规律，近期出现了网络模型与多车道模型相结合的趋势。
City traffic models have been used to investigate (phase) transition. A trend is the combining of city traffic and multi-lane models.
我们提出了一个网络上的简单交通流模型。
In this paper, we propose a simple model for traffic dynamics on networks.
在简要介绍神经网络原理的基础上，分析了采用神经网络解决交通系统中空车调度及交通流预测的原理及方法。
Based on the introduction to neural network principle, two methods of solving free train schedule and traffic flow prediction in transportation system with neural network are analyzed.
对于计算机高速网络中能控交通流的调节，PI控制器的参数优化直接影响控制系统的性能。
For the flow regulation of the controllable traffic in high-speed computer networks, optimization of control parameters directly influence on a PI controller.
文章对含权复杂网络研究的最近进展给予了评述，特别报道了文章作者最近提出的一个交通流驱动的含权技术网络模型。
We review recent progress in the research on weighted complex networks. In particular, we present our recent model of a traffic flow driven weighted technological network.
本文报道最近提出的一个交通流驱动的含权复杂网络模型及相关研究工作进展。
In this paper we report a recent proposed complex network model which is weighted and driven by traffic flow.
提出用动态回归神经网络建立高速公路宏观交通流模型。
A dynamic recurrent neural network to freeway macroscopic traffic flow modeling is presented.
介绍了用于短期交通流预测的两大类模型：统计预测算法和人工神经网络模型。
A large number of techniques have been applied into short-term traffic flow prediction, which can be classified into two groups: statistical models and artificial neural network model.
在可变需求网络中考虑交通流分配的非均衡演化过程，建立一个时变拥挤收费和道路通行能力的联合最优控制理论模型，旨在使系统的全期总收益最大。
This paper presents a joint optimization model of time varying road tolls and capacities using the optimal control theory in disequilibrium traffic networks with elastic demand.
将BP神经网络运用到自行车穿越决策模型中，丰富了混合交通流微观模型。
The BP neural network was used to the bicycles'decision-making model, enriching the micro-model of mixed traffic flow.
交通流诱导是目前公认的提高交通效率和机动性的最佳途径，其目标是在交通网络中为行人提供最优的旅行路径。
Traffic flow guidance is considered as an optimum way to improve traffic efficiency and mobility, it's purpose is to provide the best travel paths for pedestrians in the transportation network.
提出一种新的贝叶斯组合神经网络模型并将其应用于短期交通流量的预测。
Method named BAYESIAN combined neural network model is proposed for short term traffic flow prediction in this paper.
基于神经网络的交通流预测模型已被广泛应用于ITS由于其较高的预测精度和自我学习能力。
The traffic flow forecasting model based on neural network has been applied widely in its because of its high forecasting accuracy and self-learning ability.
通过对高速公路宏观动态交通流模型的分析，提出了动态交通流的神经网络模型。
By analyzing the freeway macroscopic dynamic traffic flow model, the paper presents a neural network model for traffic flow.
以交通流理论为指导思想，提出采用OPNET网络仿真软件设计网络道路交通流仿真平台。
The paper considers traffic stream theory as directive thinking and designs network road traffic stream simulating platform using OPNET network simulating software.
根据常用的高速公路交通流宏观动态模型，建立了高速公路交通流的RBF神经网络模型。
On the basis of macroscopic dynamic traffic flow model which is frequently used in traffic control, Radial basis Function (RBF) neural network is designed.
本文采用改进型BP神经网络建立起交通流的时间序列模型，该模型可用于短期内道路交通流量的预测。
In this paper, the time - sequence model of traffic flow is based on the improved BP neural network, and this model can be used for short time prediction of traffic flow.
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).
并利用一段高速公路的交通流数据对BP神经网络进行训练，得到网络参数。
Then, the BP neural network is trained by using traffic flow data from a section of freeway and the network model parameters can be obtained.
并重点研究了基于遗传—bp神经网络组合模型的二源、三源动态交通流数据融合技术。
Further, the dynamic traffic data fusion technique based on the GA-BP Model is studied for the dual-source and triple-source dynamic traffic data.
神经网络可以很好的解决交通领域内的非线性问题，其中前向型神经网络特别适合对交通流的预测。
In traffic field, Neural Network has good advantage in the non-linear Neural Network, and it 's specially good at problem perfectly solving the traffic in the field of the forward flow forecasting.
因此很容易预测交通流量通过网状网络因为他们对整个路径计算一次。
Therefore it is very easy to predict the traffic flows through the meshed network since they are calculated once for the entire path.
针对交通流量混沌时间序列多步预测的问题，提出了一种基于混沌机理的小波神经网络(WNN)快速学习算法。
Aiming at the issue about multi-step prediction of the traffic flow chaotic time series, a fast learning algorithm of wavelet neural network (WNN) based on chaotic mechanism is proposed.
交通网络模型、路径规划算法以及交通流预测是车辆导航动态路径规划需要解决的重点问题。
The key problems of vehicle navigation dynamic path planning are traffic network model, path planning algorithm and traffic flow prediction.
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.
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.
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