改进灰色模型的船舶航行轨迹自动预测研究  

Research on automatic prediction of ship trajectory based on improved grey model

作　　者：周艳萍[1] 曾宪群[1] 蔡玲[1] ZHOU Yan-ping;ZENG Xian-qun;CAI Ling(Jiangxi Biological Vocational College,Nanchang 330006,China)

机构地区：[1]江西生物科技职业学院,江西南昌330006

出　　处：《舰船科学技术》2021年第20期34-36,共3页Ship Science and Technology

摘　　要：为实现更加精准、自动化的船舶航行轨迹预测,利用改进灰色模型,提出一种基于改进灰色模型的船舶航行轨迹自动预测方法。在船舶航行中的AIS数据中对船舶航行轨迹数据进行提取,其中AIS数据具体包括船舶航程数据、船舶动态数据以及船舶动态数据。通过数据估计算法插补缺失数据,分为2个步骤,第1步是对插补数据进行识别,第2步是对其进行插补。通过改进灰色模型对船舶航行轨迹进行自动预测,主要使用基于缓冲算子改进的灰色模型构建船舶航行轨迹自动预测模型。选取某船舶服务项目中包含的船舶AIS数据作为实验数据,对设计方法进行实例测试。测试结果表明,设计方法的数据提取质量较高、预测模型的误差较小,具有广阔的市场应用前景。In order to achieve a more accurate and automated ship trajectory prediction,an improved gray model is used to propose an automatic ship trajectory prediction method based on the improved gray model.The ship’s trajectory data is extracted from the AIS data during the ship’s voyage.The AIS data specifically includes ship voyage data,ship dynamic data,and ship dynamic data.Imputation of missing data through the data estimation algorithm is divided into two steps.The first step is to identify the imputed data,and the second step is to impute it.The automatic prediction of ship trajectory is carried out by improving the gray model,and the improved gray model based on buffer operator is mainly used to construct the automatic prediction model of ship trajectory.Select the ship AIS data contained in a certain ship service project as the experimental data to test the design method.The test results show that the data extraction quality of the design method is high,the error of the prediction model is small,and it has a broad market application prospect.

关 键 词：改进灰色模型 船舶航行轨迹 缓冲算子 轨迹自动预测 缺失值处理 

分 类 号：C93[经济管理—管理学]