Forecast of Traffic Volume Based on Genetic Neural Network Optimization Model

XU Lun-hui; LIU Zheng-dong; ZHOU Wen-xia; XI Li-an

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Forecast of Traffic Volume Based on Genetic Neural Network Optimization Model

更新时间：2026-05-27

- Forecast of Traffic Volume Based on Genetic Neural Network Optimization Model
- Vol. 23, Issue 4, Pages: 1-5(2006)
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- Online First：10 November 2006，
  
  Published：2006
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许伦辉, 刘正东, 周文霞, 习利安. 基于遗传神经网络优化模型的交通量预测[J]. 广东工业大学学报, 2006, 23(4): 1-5.

XU Lun-hui, LIU Zheng-dong, ZHOU Wen-xia, et al. Forecast of Traffic Volume Based on Genetic Neural Network Optimization Model[J]. 2006, 23(4): 1-5.
许伦辉, 刘正东, 周文霞, 习利安. 基于遗传神经网络优化模型的交通量预测[J]. 广东工业大学学报, 2006, 23(4): 1-5. DOI：

XU Lun-hui, LIU Zheng-dong, ZHOU Wen-xia, et al. Forecast of Traffic Volume Based on Genetic Neural Network Optimization Model[J]. 2006, 23(4): 1-5. DOI：

摘要

实时、准确的交通量预测是实现动态交通流控制及诱导的前提和基础.为了更准确地对其进行预测

本文建立了遗传神经网络优化模型

该模型既利用遗传算法全局搜索、快速收敛的优点

又利用神经网络非线性描述、自学习自适应的优点.并以实际道路为例

给出了具体的应用方法

计算机仿真结果表明该模型精度较高、具有可行性.

Abstract

The accurate real-time forecast of traffic volume is the premise and basement of the dynamic traffic control and guidance.In order to forecast the traffic volume more accurately

this paper establishes an optimization model of genetic neural network.It not only utilizes the advantages of the genetic algorithm which are global search and rapid convergence

but also makes use of the merits of the neural network which are nonlinearly describing

self learning and self adapting.It has been applied on a real road to forecast the traffic volume and the computer simulations have proved that the optimization model has great precision and feasibility.

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references

杨兆升,谷远利. 实时动态交通流预测模型研究[J]. 公路交通科技. 1998(03)

李存军,杨儒贵,靳蕃. 基于神经网络的交通信息融合预测方法[J]. 系统工程. 2004(03)

裴玉龙,王晓宁. 基于BP神经网络的交通影响预测模型[J]. 哈尔滨工业大学学报. 2004(08)

刘洁,魏连雨,杨春风. 基于遗传-神经网络的交通量预测[J]. 长安大学学报(自然科学版). 2003(01)

朱中,杨兆升. 实时交通流量人工神经网络预测模型[J]. 中国公路学报. 1998(04)

尹宏宾,徐建闽,周其节. 遗传算法在交通量预测中的应用[J]. 中国公路学报. 1998(02)

[日]玄光男,[日]程润伟著,于歆杰,周根贵译.遗传算法与工程优化[M]. 清华大学出版社, 2004

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