Separation method of wind-wave and swell based on the multilayer perceptron

Xu Xiao; Tao Aifeng; Han Xue; Pan Xishan; Yang Yini

doi:10.12284/hyxb2023001

Volume 45 Issue 2

Feb. 2023

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Xu Xiao，Tao Aifeng，Han Xue, et al. Separation method of wind-wave and swell based on the multilayer perceptron[J]. Haiyang Xuebao，2023, 45(2)：1–12 doi: 10.12284/hyxb2023001

Citation:

Xu Xiao，Tao Aifeng，Han Xue, et al. Separation method of wind-wave and swell based on the multilayer perceptron[J]. Haiyang Xuebao，2023, 45(2)：1–12 doi: 10.12284/hyxb2023001

Citation:

Xu Xiao，Tao Aifeng，Han Xue, et al. Separation method of wind-wave and swell based on the multilayer perceptron[J]. Haiyang Xuebao，2023, 45(2)：1–12 doi: 10.12284/hyxb2023001

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Separation method of wind-wave and swell based on the multilayer perceptron

doi: 10.12284/hyxb2023001

Xu Xiao^{1, 2, 4
,},
Tao Aifeng^{1, 2
,
,},
Han Xue³,
Pan Xishan³,
Yang Yini^{1, 2}

1.
Key Laboratory of Ministry of Education for Coastal Disaster and Protection, Hohai University, Nanjing 210024, China
2.
College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210024, China
3.
Tidal Flat Research Center of Jiangsu Province, Nanjing 210036, China
4.
Port and Waterway Development Center, Department of Transportation of Jiangsu Province, Nanjing 210004, China

Received Date: 2021-06-22
Rev Recd Date: 2022-07-23

Available Online: 2022-10-19

Publish Date: 2023-02-01

Abstract

Abstract

Separation of wind-wave and swell is the basis for studying the respective characteristics of wind-wave and swell. However, due to the lack of wave spectrum data, it is difficult to popularize and apply separation methods based on wave spectrums. An effective solution is to use wave observations that are easy to obtain, namely basic wave elements to separate wind-wave and swell. Existing methods cannot use basic wave elements to comprehensively calculate the proportions and characteristic parameters of wind-wave and swell. For this reason, this paper introduces machine learning into the separation of wind-wave and swell. Based on the multi-layer perceptron model, a method using wave elements and wind elements to accurately estimate wind-wave and swell parameters is proposed. This method requires each station to provide at least 466 training samples of wave data and 766 or more training samples are recommended. The method is suitable for 3 stations in the Taiwan Strait with its accuracy significantly better than traditional methods based on wave spectrums. The proposed method can provide alternative calculation schemes of wind-wave and swell for stations lacking wave spectrums in this sea area. It helps expand the source of measured data of wind-wave and swell, therefore strengthening the research on the characteristics and early warning and forecasting of wind-wave and swell.
- separation of wind-wave and swell,
- Taiwan Strait,
- machine learning,
- swell,
- wind-wave

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References(27)

References

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