Identification of Noise Points in Buoy Telemetry Position Data Based on PSO-DBSCAN Algorithm

Buoys are artificial signs that guide the navigation of ships,and are of great significance to ensuring the safety of ships.The effective use of the buoy telemetry position data can analyze the offset characteristics of the buoy and improve the buoy's navigation aid efficiency.However,due to the influence of data transmission or human factors,the buoy telemetry data often contains noise points,which affects the application of buoy telemetry position data.To identify noise points in buoy telemetry position data,a DBSCAN algorithm optimized by particle swarm optimization is proposed,and the input parameters are determined adaptively to realize the identification of noise points in the buoy telemetry position data.Experiments on the relative buoy telemetry position data in Xiamen Port show that the PSO-DBSCAN algorithm can accurately identify the noise points in the buoy telemetry position data,and its effect is consistent with the actual situation.