Short –term Prediction Of Available Parking Space Based On Improved Wavelet Neural Network
ID:1572 View Protection:ATTENDEE Updated Time:2021-12-03 13:41:17 Hits:217 Poster Presentation

Start Time:Pending(Asia/Shanghai)

Duration:Pending

Session:No Session »

No files

Abstract
Accurate short-term prediction of available parking space (APS) is the basic theory of parking guidance information system (PGIS). This study collected the data on parking availability at several on-street parking space at 12th AVE, Settle, America to investigate the changing characteristics of APS, and predicted the APS based on improved wavelet neural network (WNN). It presents an improved WNN algorithm with wavelet (WA) decomposition and particle swarm optimization (PSO). The original time series was decomposed and reconstructed by wavelet analysis, and the WNN algorithm finds the optimal threshold of initial weight through PSO. Compared with the methods of BPNN, WNN, PSO-WNN, the WA-PSO-WNN algorithm performs much better on predicting accuracy and stability. Keywords: APS, short-term prediction, wavelet analysis, particle swarm optimization, wavelet neural network
Keywords
CICTP
Speaker
Jinfen Wang
Ningbo University

Submission Author
Jinfen Wang Ningbo University
Submit Comment
Verify Code Change Another
All Comments
Important Date
  • Conference Date

    Dec 17

    2021

    to

    Dec 20

    2021

  • Dec 16 2021

    Contribution Submission Deadline

  • Dec 24 2021

    Registration deadline

Sponsored By
Chinese Overseas Transportation Association
Chang'an University
Contact Information