Prediction of ocean waves in Hong Kong western waters by using artificial neural networks

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Prediction of ocean waves in Hong Kong western waters by using artificial neural networks

 

Author: Tam, Chin-hung
Title: Prediction of ocean waves in Hong Kong western waters by using artificial neural networks
Degree: M.Sc.
Year: 2000
Subject: Ocean waves -- China -- Hong Kong
Neural networks (Computer science) -- China -- Hong Kong
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Dept. of Civil and Structural Engineering
Pages: viii, 103 leaves : ill. ; 30 cm
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b1517969
URI: http://theses.lib.polyu.edu.hk/handle/200/4068
Abstract: The potential of using artificial neural networks (ANNs) with back-propagation algorithm and time delay technique for prediction of ocean waves in Kau Yi Chau (KYC) and West Lamma Channel (WLC), Hong Kong is explored. MATLB with Neural Network Toolbox 3.0 was employed to develop the ANNs. Hourly significant wave height and corresponding wind parameters of each location were placed in the ANN. Because of instruments failure or servicing, the data must have been missed. The interpolation method had to be employed in order to fill in the data gap. The interpolated data were filled in only within two-hour gap. Each location of data was divided into two categories. One of the categories used the whole set of data to develop a wind-generated waves network. Another category used the high-waves data (>= 1 m) to develop high-waves network. Each set of data was also divided into training, validation and testing sets. During the ANNs manipulation, three layers of ANN were employed. The error measurement of the ANNs performance and training rule was based on the default mean squared errors (MSE) and Marquardt-Levenberg respectively in MATLAB. Different transfer functions and number of neurons were also tested in order to improving output accuracy. The results were analyzed by statistical method, such as mean error (ME), average error, mean squared errors (MSE), residual standard error (RSE), coefficient of determination (R2) and F - test. After the statistic analysis, two individual Kau Yi Chau networks were developed for general condition (3 layers with 5-time delay, 10-20-1, tansig: logsig: purlin) and high-waves situation (3 layers with 3-time delay, 3-15-1, tansig: logsig: purlin). During the general condition in KYC network, the percentage of average error and the coefficient of determination was 28.19% and 0.3732 respectively. Moreover, the percentage of average error and the coefficient of determination was 9.63% and 0.2323 respectively during high-waves situation. One network was developed only for West Lamma Channel during general condition (3 layers with 15-time delay, 10-15-1, tansig: tansig: purlin). The percentage of average error and the coefficient of determination was 32.27% and 0.2475 respectively. The results of F -test were positive in all of the three networks. They inferred that they had a statistically significant relationship between wind and wave.

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