Abstract
To analyze the changing characteristics of ship traffic flow in wind farms water area, and to improve the accuracy of ship traffic flow prediction, a Gated Recurrent Unit (GRU) of a Recurrent Neural Network (RNN) was established to analyze multiple traffic flow sections in complex waters based on their traffic flow structure. Herein, we construct a spatiotemporal dependence feature matrix to predict ship traffic flow instead of the traditional ship traffic flow time series as the input of the neural network. The model was used to predict the ship traffic flow in the water area of wind farms in Yancheng city, Jiangsu Province. Autoregressive Integrated Moving Average (ARIMA), Support-Vector Machine (SVM) and Long Short-Term Memory (LSTM) were chosen as the control tests. The GRU method based on the spatiotemporal dependence is more accurate than the current mainstream ship traffic flow prediction methods. The results verify the reliability and validity of the GRU method.
Highlights
Marine wind energy is a green renewable resource that has the advantages of cleanliness, low development cost, and abundant reserves [1,2]
The research on ship navigation safety in the water area of wind farms mainly focuses on exploring the variation law of collision risk between ships and offshore wind turbines [8,9]
As the final optimization goal of the model, the optimal spatial threshold is determined; (7) Results and analysis: To quantitatively analyze the prediction results and the performance of the model, the Mean Absolute Error (MAE), Root-Mean-Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and R2 are used as prediction and evaluation indicators
Summary
Marine wind energy is a green renewable resource that has the advantages of cleanliness, low development cost, and abundant reserves [1,2]. With the development of offshore wind power technology, offshore wind farm construction has gradually become a key development field [3]. With the increasing frequency of offshore wind power construction, the risk assessment of ship navigation in wind farms water area has attracted the attention of scholars at home and abroad [4]. With the increase in offshore wind power construction, the safety of ship navigation in the waters of offshore wind farms has gradually attracted the extensive attention of relevant scholars. The research on ship navigation safety in the water area of wind farms mainly focuses on exploring the variation law of collision risk between ships and offshore wind turbines [8,9]
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