Trajectory Data-based Inland Container Ships Navigation Efficiency Mining And Analysis

With the adjustment of industrial structure and the rapid development of inland economy,the demand for inland waterway transport in China is increasing.At the same time,the high quality development of inland shipping industry also put forward higher requirements for inland river navigation efficiency.To ensure the efficient navigation of ships in inland rivers,on the one hand,it can reduce oil consumption and reduce carbon emissions,on the other hand,it can improve the efficiency of ship circulation,increase the operating efficiency of ships,and improve the economic benefits of inland Shipping Co and inland river ports.With the development of shipping information technology,mass shipping data is constantly emerging.The ship trajectory data generated by the Automatic Identification System(AIS)is one of them.It includes ship calling sign,ship name,ship position,ship type,navigation speed and so on.These data provide a solid data base for shipping related research.In order to improve the navigation efficiency of inland river container ships,this paper uses SQL Server 2014 and R to unfold data mining and statistical analysis of the AIS trajectory data of the container ships in the water traffic management and monitoring system of Chongqing.The main tasks completed in this paper include:(1)This paper summarizes the domestic and international shipping industry development and research of track data.On the basis of reading a lot of documents,it is clear that the feasibility and necessity of navigation efficiency research based on trajectory big data.And determine the relevant theories and software technologies that need to be used in the research.(2)Setting up a trajectory data mining environment.First,introduce related conceptual parameters and sources of track data.Second,design the Yangtze River container transport network fence model and container ship efficiency evaluation index system.Third,construct the track database of the Yangtze River container transport network.Finally,draw the data mining logic diagram of container ship trajectory.(3)Data preprocessing is done for track data in database.Then,based on the Yangtze River container transportation network trajectory database,we design data mining method.From the Yangtze River channel as a whole,the port,wharf and ship lock are used as nodes in the channel,and the trajectory data is converted into the track line data to excavate the time characteristics of the container ship behavior.Finally,through DBSCAN clustering algorithm and artificial statistics test,it is proved that this method has restored the container ship behavior with high accuracy.(4)From the three aspects of basic data,classification according to the name of the fence,and according to the classification of Shipping Co,we conduct statistical analysis and visual display of the results of trajectory data mining.The information contained in the data is introduced,and the shortcomings in the shipping process are discovered through data analysis.Finally,through the data mining of the container ship trajectory,this paper finds that the shipping industry of the Yangtze River has some problems such as low navigation efficiency of part of the Shipping Co,the low efficiency of part of the port operation and the long waiting time of passing through the lock.And the corresponding strategies are put forward for the various links of the Yangtze River shipping.