Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17008
Title: Application of artificial neural network to numerical wave prediction
Authors: Qi, YQ
Zhang, ZX
Li, CW 
Li, YS 
Shi, P
Keywords: Artificial neural network
Numerical prediction
Numerical wave model
Significant wave height
Issue Date: 2005
Publisher: 中國學術期刊(光盤版)電子雜誌社
Source: 水科學進展 (Advances in water science), 2005, v. 16, no. 1, p. 32-35 How to cite?
Journal: 水科學進展 (Advances in water science) 
Abstract: The objective of this paper is to use an artificial neural network (ANN) model to train the output of a third generation wave model to better forecast the significant wave heights from buoy data. After training, the agreement between the wave model's output and the buoy data generally increases, but there is still significant disagreement when the wave height is at its peak. The significant wave heights bigger than 1.5m are selected to retrain, using the same ANN model, and the resulting improvement in the forecast is obvious since the root mean square error (RMS) between the ANN output and the buoy data decrease from 0.31 m to 0.29 m. The goal of this paper is to investigate the feasibility of using an ANN to improve a wave model's numerical wave prediction so as to develop a more accurate wave forecasting system. The results show that an ANN is an useful tool for this purpose.
URI: http://hdl.handle.net/10397/17008
ISSN: 1001-6791
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

1
Last Week
0
Last month
Citations as of Sep 16, 2017

Page view(s)

42
Last Week
1
Last month
Checked on Sep 17, 2017

Google ScholarTM

Check



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.