A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
A Comparison of Ocean Wave Height Forecasting Methods for Ocean Wave Energy Conversion Systems
Ocean wave height plays an important role in the operation status of ocean wave energy conversion systems. In this paper, the future continuous ocean wave height within 2~3 s is forecasted by three methods, the autoregressive moving average model (ARMA) method, backpropagation (BP) neural network method, and radial basis function (RBF) neural network method. Then, the error between suggested forecast results and corresponding measured results are compared by the root mean square error (RMSE), mean absolute error (MAE), and correlation coefficient R. The comparison result indicates that the RBF neural network method is preferred to the other two methods, having the advantage of high accuracy. Lastly, the reasons for the errors of the three forecasting methods are analyzed. This study signifies that the RBF neural network method is beneficial to the operation control and efficiency improvement of ocean wave energy conversion systems.
A Comparison of Ocean Wave Height Forecasting Methods for Ocean Wave Energy Conversion Systems
Ocean wave height plays an important role in the operation status of ocean wave energy conversion systems. In this paper, the future continuous ocean wave height within 2~3 s is forecasted by three methods, the autoregressive moving average model (ARMA) method, backpropagation (BP) neural network method, and radial basis function (RBF) neural network method. Then, the error between suggested forecast results and corresponding measured results are compared by the root mean square error (RMSE), mean absolute error (MAE), and correlation coefficient R. The comparison result indicates that the RBF neural network method is preferred to the other two methods, having the advantage of high accuracy. Lastly, the reasons for the errors of the three forecasting methods are analyzed. This study signifies that the RBF neural network method is beneficial to the operation control and efficiency improvement of ocean wave energy conversion systems.
A Comparison of Ocean Wave Height Forecasting Methods for Ocean Wave Energy Conversion Systems
Qin Guodong (author) / Chen Zhongxian (author)
2023
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Ocean wave energy conversion : resource, technologies and performance
| UB Braunschweig | 2017
Deep ocean wave energy conversion using a cycloidal turbine
| Elsevier | 2011
Deep ocean wave energy conversion using a cycloidal turbine
| Online Contents | 2011
Increase of Wave Height in the North Pacific Ocean
| British Library Conference Proceedings | 1999