船舶操作预报中数据挖掘算法的应用与实现

Application and implementation of the algorithm in data mining ship operating forecasts

在现代海上交通管理中,船舶航行操控对整个航道的安全非常重要,因此只有充分挖掘海量的操作数据,才能有效实现船舶的航行安全。本文从海上交通的角度对船舶的操作行为模式展开研究,利用数据挖掘技术对AIS系统的数据进行分析,从而实现对船舶行为的预测,监测的数据主要有船舶的航行位置、船舶状态的监测和船队数量的识别等。通过仿真对特定港口的船舶数量进行大数据预测,从而能够提前预报,有效提高港口的管理水平。

In modern maritime traffic management,navigation to steer the ship of the entire waterway safety is very important,so only fully exploit the massive operational data,in order to effectively implement the safe navigation of the ship. From sea traffic point of view of the operating behavior of the ship a study,using data mining techniques to data AIS system is analyzed,enabling the ship behavior prediction,monitoring the data are sailing the ship's position,monitoring and ship status fleet number recognition. By the end the simulation of a specific number of ports the ship' s large data prediction,which can predict in advance,effectively improve the level of port management.