Cluster Analysis on the Flow Velocity for the Sea Route Monitorin

Due to the importance of the marine resources, the limited sea routes are valuable for the marine transportation. With sensors deployed under the sea, the data of flow velocity are obtained via wireless communications. Based on the real historical data collected from Qinhuangdao port, which is one of the most important ports in the North China, the rules is attempted to be revealed with the data mining methods. By cluster analysis on the historical data, we classifies the days into P-days and F-days. In different kinds of days, the characteristics of the flow velocity under the water are different. It is a novel analysis of the data for the sea route monitoring. Although it is only a preliminary exploration in this field, the result is helpful to the safety and efficiently scheduling of the sea routes.