A hybrid EMD-AR model for nonlinear and non-stationary wave forecasting

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作者：Wen-yang Duan ; Li-min Huang ; Yang Han…
关键词：Wave forecast ; Nonlinear and non ; stationary ; Autoregressive (AR) model ; Empirical mode decomposition (EMD) ; EMD ; AR model ; 波浪预报 ; 非线性和非平稳性li> 自回归模型li> 经验模态分解li> 经验模态分解自回归模型 ; U66
刊名：Journal of Zhejiang University - Science A
出版年：2016
出版时间：February 2016
年：2016
卷：17
期：2
页码：115-129
全文大小：1,007 KB
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作者单位：Wen-yang Duan (1)
Li-min Huang (1)
Yang Han (1)
De-tai Huang (1)

1. Department of Shipbuilding Engineering, Harbin Engineering University, Harbin, 150001, China

刊物类别：Engineering

刊物主题：Physics
Mechanics, Fluids and Thermodynamics
Chinese Library of Science

出版者：Zhejiang University Press, co-published with Springer

ISSN：1862-1775

文摘

Accurate wave forecasting with a couple of hours of warning time offers improvements in safety for maritime operation-related activities. Autoregressive (AR) model is an efficient and highly adaptive approach for wave forecasting. However, it is based on linear and stationary theory and hence has limitations in forecasting nonlinear and non-stationary waves. Inspired by the capability of empirical mode decomposition (EMD) technique in handling nonlinear and non-stationary signals, this paper describes the development of a hybrid EMD-AR model for nonlinear and non-stationary wave forecasting. The EMDAR model was developed by coupling an AR model with the EMD technique. Nonlinearity and non-stationarity were overcome by decomposing the wave time series into several simple components for which the AR model is suitable. The EMD-AR model was implemented using measured significant wave height data from the National Data Buoy Center, USA. Prediction results from various locations consistently show that the hybrid EMD-AR model is superior to the AR model. This demonstrates that the EMD technique is effective in processing nonlinear and non-stationary waves. Keywords Wave forecast Nonlinear and non-stationary Autoregressive (AR) model Empirical mode decomposition (EMD) EMD-AR model