The actual traffic prediction method based on particle swarm optimisation and wavelet neural network

被引：0
|
作者：
Chen K. [1 ]
Peng Z. [1 ]
Ke W. [1 ]
机构：
[1] Department of Computer Science and Technology, Guangdong University of Petrochemical Technology, Guangdong
来源：
International Journal of Wireless and Mobile Computing | 2019年 / 17卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Congestion; Neural network; Particle swarm; Prediction;
D O I：
10.1504/IJWMC.2019.103109
中图分类号：
学科分类号：
摘要：
For the congestion phenomena of networks, it has been provided with a new prediction method for service flow (based on Particle Swarm Optimisation and Wavelet Neural Network Prediction PSOWNNP). Firstly, this method is using the wavelet exchange to resolve the service flow, and using its wavelet coefficient and metric coefficient as the sample data. Secondly, training the sample data is using the neural network method of the particle swarm optimisation in which it is applying the wavelet model for construction, and the prediction data for service flow will be obtained from this. At the same time, the prediction methods of wavelet neural network and BP neural network for particle swarm optimisation are analysed and compared through the simulation experiment, and the result for indicating the performance of AWNNP method is relatively good, with a tolerance of 17.21%. Copyright © 2019 Inderscience Enterprises Ltd.
引用
收藏
页码：317 / 322
页数：5
相关论文
共 50 条
  • [21] Wavelet Neural Network Based Traffic Prediction for Next Generation Network
    赵其刚
    李群湛
    何正友
    Journal of Southwest Jiaotong University, 2005, (02) : 13 - 18
  • [22] Recurrent wavelet neural network controller with improved particle swarm optimisation for induction generator system
    Teng, L. -T.
    Lin, F. -J.
    Chiang, H. -C.
    Lin, J. -W.
    IET ELECTRIC POWER APPLICATIONS, 2009, 3 (02) : 147 - 159
  • [23] Traffic flow prediction method of road construction section based on Wavelet Neural Network
    Liu Y.
    Li H.Z.
    Advances in Transportation Studies, 2021, 2021 (Special issue 1): : 69 - 80
  • [24] Traffic Signal Prediction Using Elman Neural Network and Particle Swarm Optimization
    Ghasemi, J.
    Rasekhi, J.
    INTERNATIONAL JOURNAL OF ENGINEERING, 2016, 29 (11): : 1558 - 1564
  • [25] Particle Swarm Optimization RBF Neural Network Model for Internet Traffic Prediction
    He, Tao
    Dan, Tangren
    Wei, Yong
    Li, Huazhong
    Chen, Xu
    Qin, Guorong
    2016 INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION, BIG DATA & SMART CITY (ICITBS), 2017, : 521 - 524
  • [26] Prediction of traffic flow based on the EMD and wavelet neural network
    Feng, Teng
    Wang, Xiaohong
    He, Yunlai
    PROCEEDINGS OF THE 2015 2ND INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER ENGINEERING AND ELECTRONICS (ICECEE 2015), 2015, 24 : 933 - 938
  • [27] Particle swarm optimisation for evolving artificial neural network
    Zhang, CL
    Shao, HH
    Li, Y
    SMC 2000 CONFERENCE PROCEEDINGS: 2000 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOL 1-5, 2000, : 2487 - 2490
  • [28] Erratum to: Application of particle swarm optimisation in artificial neural network for the prediction of tool life
    U. Natarajan
    R. Saravanan
    V. M. Periasamy
    The International Journal of Advanced Manufacturing Technology, 2017, 90 : 2411 - 2411
  • [29] Prediction for network traffic of radial basis function neural network model based on improved particle swarm optimization algorithm
    Weijie Zhang
    Dengfeng Wei
    Neural Computing and Applications, 2018, 29 : 1143 - 1152
  • [30] Prediction for network traffic of radial basis function neural network model based on improved particle swarm optimization algorithm
    Zhang, Weijie
    Wei, Dengfeng
    NEURAL COMPUTING & APPLICATIONS, 2018, 29 (04): : 1143 - 1152
12345