Application research of unmanned ship route dynamic planning based on meteorological big data

In order to realize that unmanned cargo ship can move forward according to the optimal route and reduce the risk in the harsh environment of wind and wave, a D* algorithm for dynamic route planning based on A* static route planning is proposed. Firstly, spark big data processing platform is built. The big data platform is used to preprocess data, extract effective features and build weather forecast models. In the construction of weather forecast model, the commonly used forecasting models are used to predict and optimize the optimal model parameters. Select the F1 value of each model for comparison, and then select the model with the highest F1 value in each period as the prediction model of the period according to the characteristics of weather data. Finally, the results of multiple models are summarized to form the final weather forecast data set. Then, according to the starting point and terminal point, combined with D* dynamic programming algorithm, a safe and shortest route is planned when the threat changes constantly.