摘要
基于船舶自动识别系统(AIS)大数据,通过解析AIS原始报文,分离出关键字条,经过数据清洗、筛选后匹配其他船舶数据源,以进一步识别船舶类型并划分吨级。将大数据应用于船舶流量预测中,通过跟踪代表船型的航迹,总结出船舶航行规律和运营情况,再结合历史数据和宏观形势发展,综合预测航道货运量,基于对AIS数据的挖掘,运用分配模型预测多汊航道船舶流量,并以长江口南槽航道为例预测其船舶流量。结果表明,运用AIS大数据能有效分析复杂多变的船舶航路,从而准确地预测多汊道航道船舶流量。
Based on automatic identification system( AIS) big data,this paper analyzes the AIS original message,separates the keywords,and matches other ship data sources after data cleaning and filtering to further identify the ship type and divides by tonnage. Applying big data to the prediction of ship flow,this paper tracks the ship’ s trajectory, summarizes the ship ’ s navigation law and operation, combines historical data with the development of the macro situation to comprehensively forecast the volume of waterway freight,predicts the ship flow in multi-branch channel by allocation model,and takes the south passage channel of the Yangtze Estuary as an example to predict the ship flow. The results show that AIS big data can be used to analyze the complicated and changeable ship routes,so as to accurately predict the ship flow in the multi-branch channel.
作者
袁子文
YUAN Zi-wen(Transport Planning and Research Institute,Ministry of Transport,Beijing 100028,China)
出处
《水运工程》
北大核心
2020年第9期152-157,共6页
Port & Waterway Engineering