Journal of Risk Analysis and Crisis Response

Volume 3, Issue 4, December 2013, Pages 185 - 191

WD-RBF Model and its Application of Hydrologic Time Series Prediction

Authors
Dengfeng Liu, Dong Wang, Yuankun Wang, Lachun Wang, Xinqing Zou
Corresponding Author
Dong Wang
Received 15 September 2013, Accepted 12 December 2013, Available Online 27 December 2013.
DOI
https://doi.org/10.2991/jrarc.2013.3.4.4How to use a DOI?
Keywords
Hydrologic time series, RBF network, Wavelet de-noising, Water hazards
Abstract
Accurate prediction for hydrological time series is the precondition of water hazards prevention. A method of radial basis function network based on wavelet de-nosing (WD-RBF) was proposed according to the nonlinear problem and noise in hydrologic time series. Wavelet coefficients of each scale were calculated through wavelet transform; soft-threshold was used to eliminate error in series. Reconstructed series were predicted by RBF network. The simulation and prediction of WD-RBF model were compared with ARIMA and RBF network to show that wavelet de-nosing can identify and eliminate random errors in series effectively; RBF network can mine the nonlinear relationship in hydrologic time series. Examples show that WD-RBF model has superiority in accuracy compared with ARIMA and RBF network.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Journal
Journal of Risk Analysis and Crisis Response
Volume-Issue
3 - 4
Pages
185 - 191
Publication Date
2013/12/27
ISSN (Online)
2210-8505
ISSN (Print)
2210-8491
DOI
https://doi.org/10.2991/jrarc.2013.3.4.4How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Dengfeng Liu
AU  - Dong Wang
AU  - Yuankun Wang
AU  - Lachun Wang
AU  - Xinqing Zou
PY  - 2013
DA  - 2013/12/27
TI  - WD-RBF Model and its Application of Hydrologic Time Series Prediction
JO  - Journal of Risk Analysis and Crisis Response
SP  - 185
EP  - 191
VL  - 3
IS  - 4
SN  - 2210-8505
UR  - https://doi.org/10.2991/jrarc.2013.3.4.4
DO  - https://doi.org/10.2991/jrarc.2013.3.4.4
ID  - Liu2013
ER  -