traffic-flow prediction 交通流量预测
Elevator traffic flow prediction 电梯交通流预测
short time traffic flow prediction 短时交通流量预测
In recent years, the grey prediction model is favored by the traffic flow prediction researchers owing to simpler algorithm, less required data and computing time.
近年来,灰色预测模型以其算法简单,所需数据少,运算时间短的优点受到交通流预测研究人员的青眯。
参考来源 - 基于灰色预测模型的短期交通流预测研究Based on the phase space reconstruction improved by wavelet transformation, this paper takes influence of wavelet denoising into account, and introduces the method of chiastic time series predictor based on wavelet neural network traffic flow prediction.
在Takens提出的相空间重构模型基础上，应用小波变换对其进行改进，充分考虑噪声对重构结果的影响。 将小波神经网络混沌时间序列预测方法引入网络流量预测中，介绍小波神经网络的基本构造和学习方法。
参考来源 - 基于小波神经网络的流量混沌时间序列预测Short—term traffic flow prediction is the basis of dynamic traffic control and guidance.
短时交通流预测是动态交通控制和诱导的前提。
参考来源 - 基于BP神经网络的城市交通流量预测与路口分析·2,447,543篇论文数据，部分数据来源于NoteExpress
Short—term traffic flow prediction is the basis of dynamic traffic control and guidance.
短时交通流预测是动态交通控制和诱导的前提。
The precondition and key of intelligent control of urban traffic is real time and exact traffic flow prediction.
城市交通的智能控制实现的前提和关键是实时准确的交通流量预测。
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。
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