长江上海段异常船舶识别研究  

Study on the Abnormal Vessel Identification in the Shanghai Section of the Yangtze River

作　　者：赖俊东 刘玢炜 许彦旻 杨金龙 LAI Jun-dong;LIU Fen-wei;XU Yan-min;YANG Jin-long(Shanghai Tobacco Group Co.,Ltd.,Shanghai 200082,China;School of Artificial Intelligence and Computer Science,Jiangnan University,Wuxi 214122,China)

机构地区：[1]上海烟草集团有限责任公司,上海200082 [2]江南大学人工智能与计算机学院,江苏无锡214122

出　　处：《电脑与信息技术》2024年第5期27-30,共4页Computer and Information Technology

摘　　要：针对长江上海段的船舶异常问题,提出了一种基于多元大数据技术的判断模型。现有异常船舶识别方法存在数据孤岛难题,难以发现有效关联关系,基于此,研究长江上海段异常船舶识别方法。首先,基于多元大数据技术整合船舶航迹信息、人船关联信息等多个数据源,并利用粒子群优化模糊神经网络实现异常船舶识别。实验结果表明,设计方法的识别精度最高达到了93%,具有一定的实用性。This study proposes a judgment model based on multiple big data technology for the problem of ship ships in Shanghai section of the Yangtze River.The existing abnormal ship identification method has the problem of data island,and it is difficult to find the effective correlation.In this regard,the identification method of abnormal ship in the Shanghai section of the Yangtze River is studied.First of all,integrate multiple data sources such as ship track information and human-ship correlation information based on multi-big data technology,and optimize fuzzy neural network based on particle swarm.The experimental results show that the identification accuracy of the design method is 93%,which has certain practicability.

关 键 词：多元大数据 粒子群优化模糊神经网络 异常船舶识别 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] U675.7[自动化与计算机技术—计算机科学与技术]