The traffic prediction in Wireless Sensor Network(WSN) is important to WSN management.
无线传感器网络（WSN）的流量预测研究对WSN管理有重要的意义。
Traffic prediction has significant meanings for management, layout and design of largescale network.
网络流量预测对大规模网络管理、规划、设计具有重要意义。
In this paper, a method of network traffic prediction based on wavelet transform and autoregressive model is proposed.
本文前言部分，主要介绍了网络流量预测的研究背景及本文的工作。
The experimental results prove that the model is efficient in network traffic prediction with good astringency and stability.
实验结果表明，该模型对网络流量的短期预测是有效可行的，并具有良好的收敛性和稳定性。
The traditional methods of network traffic prediction are to build mathematical models using its statistical characteristics.
网络流量预测传统方法是利用流量的统计特性建立数学模型。
As one of the main contents of service management, traffic prediction plays an important role in network layout, traffic management etc.
网络流量预测在网络规划、流量管理等方面起着重要的作用，是业务管理的主要研究内容之一。
Many researches have been made on VBR dynamic bandwidth allocation, but most of them focus on traffic prediction, not on traffic QOS guarantees.
以往的VBR动态带宽分配模型中多只注重对VBR业务的预测研究，而忽视分配机制对业务的QOS参数影响。
At the same time this paper is also a beneficial trying on the application of classifiers combination technology in the traffic prediction field.
同时也是将分类器组合技术应用到交通预测领域的有益尝试。
The performances of some classic time series prediction models were analyzed together concerning the traffic prediction of General Packets Radio Service (GPRS) cells.
针对通用无线分组业务(GPRS)小区流量预测问题，对几种典型时序预测模型的性能进行了综合分析。
This article has built a new traffic prediction model considering the location factors in traffic districts, compared it with the traditional analytical method through numerical examples.
文章在考虑了各交通小区的区位因素后，建立了一种新的交通预测模型。
This paper focuses on the ABR(Available bit rate) congestion control algorithm in the satellite ATM network based on onboard processing, which is implemented by using the traffic prediction.
本文主要研究基于星上处理的卫星ATM网的ABR流量控制，它通过对流量的长时预测来达到控制目的。
In 2006 the Land Transport Authority tested a traffic-prediction system built by IBM to set the tolls.
2006年，陆路交通管理局测试了一套由ibm公司制造的用于设置收费额的交通预测系统。
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.
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。
In response to various characteristics of the present road traffic flow prediction, a combined prediction is presented in this article.
针对当前道路交通流量预测的多种不同特性的方法，提出了一种组合预测方法。
With more and more traffic accidents appearing in China, the prediction of road traffic safety is more and more important for planning and decision on road traffic safety.
随着我国交通事故的大幅增多，道路交通事故预测对道路交通安全的规划、决策具有重要的现实意义。
A grey prediction model GM (1, 1) using grey system theory was created to predict the traffic conflicts. Its feasibility was tested by some related tests.
本文将灰色系统理论应用于交通冲突数的预测，建立了交通冲突数的GM(1,1)预测模型，并通过相关检验验证了该方法的可行性。
Precision prediction capability for trajectory is the base of software for air traffic control.
精确的航迹预测能力是空中交通管制软件的开发基础。
This paper proposes a new dynamic traffic congestion prediction model.
提出了一种新的动态交通拥挤预测模型。
Then sensitivity analysis on the factors of temperature and traffic loading is conducted and a short-term rutting prediction model is developed.
分析过程中进行了路面车辙的温度和交通敏感性分析，并进行了针对其短期发生过程的预估模型研究。
The importance of road traffic accident prediction is described and the shortcomings of traditional predicting methods are discussed.
指出了预测对道路交通安全性的重要意义以及传统预测方法存在的缺陷；
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。
Highway traffic noise prediction model is deduced and analyzed. It is indicated that the FHWA model originating from USA Federal Highway Administration is an approximate representation.
对公路交通噪声预测模型进行了分析推导，指出美国联邦公路局FHWA模型为近似表达式，并给出了精确表达式。
The present thesis provides a method to predict the traffic flow in a short period by combining several prediction models and artificial intelligence.
本文提出了一种将多种预测模型与人工智能技术相结合的短时交通流智能预测方法。
Method named BAYESIAN combined neural network model is proposed for short term traffic flow prediction in this paper.
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。
Considering the nonlinearity, complexity and randomicity of elevator traffic flow, the prediction model of elevator traffic flow based on wavelet support vector machines was proposed.
考虑到电梯交通流本身所存在的非线性、复杂性和随机性，提出了一种基于小波支持向量机的电梯交通流预测模型。
It makes a comparison between the SCV and packet number prediction effect of real traffic load of NLANR and the effect on the total traffic load estimation.
通过分析数据源nlanr给出的真实网络流量数据，比较SCV和分组数的预测效果，以及对网络流量估计的影响。
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.
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。
Through comparing various domestic and international traffic noise prediction models, a revised forecast model was selected to predict theoretical noise value.
在比较国内外各种道路交通噪声预测模型特点的基础上，选择了一种修正预测模型，预测出理论噪声值。
According to the traffic characteristics in big cities where the advanced urban traffic control system have been installed, a real-time traffic volume fuzzy prediction system is proposed.
针对安装了先进的交通控制系统的城市的交通持点，设计了一个实时流量模糊预测系统。
According to the traffic characteristics in big cities where the advanced urban traffic control system have been installed, a real-time traffic volume fuzzy prediction system is proposed.
针对安装了先进的交通控制系统的城市的交通持点，设计了一个实时流量模糊预测系统。
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