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A Spatial Framework for Extracting Suez Canal Transit Information from AIS

机译:从AIS中提取苏伊士渠道过境信息的空间框架

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The Suez Canal is one of the world’s most important maritime routes, as shown by the almost 19,000 transits made every year. Despite its importance to seaborne trade, few statistics about the operation are available. This paper outlines a method to generate transit information from the matching of Automatic Identification System (AIS) ship tracking data and the modeled spatial environment of the Suez Canal. Additionally, important features such as the waiting time at anchor and the access routes to the Canal are extracted from adjustments to Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. The algorithm is designed to be deployed in a distributed setting for the handling of big data sets.
机译:Suez Canal是世界上最重要的海上航线之一,正如每年近19,000次进行的。尽管对海运贸易重视,但很少有关于该操作的统计数据。本文概述了一种从自动识别系统(AIS)船舶跟踪数据匹配和苏伊士运河的模型空间环境中生成过境信息的方法。另外,从噪声(DBSCAN)算法的应用的基于密度的空间聚类,提取诸如锚的等待时间的重要特征以及对运河的接入路线。该算法旨在部署在分布式设置中以处理大数据集。

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