Study of Real-Time Traffic Flow Prediction Based on Wavelet Fuzzy Neural Networks
CSTR:
Author:
  • Article
  • | |
  • Metrics
  • |
  • Reference [10]
  • |
  • Related [20]
  • | | |
  • Comments
    Abstract:

    Real-time traffic flow prediction is one of important contents of intelligent transportation system research. Combined with the related knowledge of wavelet analysis and fuzzy neural networks, this paper gives the traffic flow forecasting model based on wavelet fuzzy neural networks. It takes wavelet function as fuzzy membership function, uses neural networks to realize fuzzy reasoning, and finishes the estimation of next cyclical traffic flow. Simultaneously the genetic algorithm is used to optimize the overall network. After the field data test, this method has high forecasting precision, stable convergence process, strong adaptability.

    Reference
    1 朱凤华.智能交通系统发展研究.中国自动化学会.2010- 2011控制科学与工程学科发展报告.北京:中国科学技术出版社,2011:126-131.
    2 贺国光,李宇,马寿峰.基于数学模型的短时交通流预测方法探讨.系统工程理论与实践,2000,20(12):51-56.
    3 Tchrakian TT, Basu B. Real-time traffic flow forecasting using spectral analysis. IEEE Trans. on Intelligent Transportation Systems, 2012, 13(2): 519-526.
    4 Quek C, Pasquier M, BBS Lim. Pop-traffic: A novel fuzzy neural approach to road traffic analysis and prediction. IEEE Trans. on Intelligent Transportation Systems, 2006, 7(2): 133-146.
    5 杨立才,贾磊,何立琴,孔庆杰.基于混沌小波网络的交通流预测算法研究.山东大学学报(工学版),2005,35(2):46-49.
    6 李婧瑜,李歧强,侯海燕,杨立才.基于遗传算法的小波神经网络交通流预测.山东大学学报(工版),2007,37(2):109-112.
    7 杨芳明,朱顺应.基于小波的短时交通流预测.重庆交通学院学报,2006,25(3):99-102.
    8 周永华.交通流预测控制机制与方法.中国公路学报,2007, 20(1):107-111.
    9 蔡磊,戴革林,陆廷金,袁冬根.模糊小波神经网络控制器在隧进殉爆控制系统中的应用.电光与控制,2009,16(1): 59-62.
    10 安治永,李应红,吴利容.基于混沌遗传算法的飞机高原滑跃起飞跑道优化设计.电光与控制,2006,13(4):52-56.
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation

邵俊倩.基于小波模糊神经网络的实时交通流预测.计算机系统应用,2016,25(7):161-164

Copy
Share
Article Metrics
  • Abstract:1336
  • PDF: 2078
  • HTML: 0
  • Cited by: 0
History
  • Received:November 19,2015
  • Revised:December 28,2015
  • Online: July 21,2016
Article QR Code
You are the first990615Visitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063