Robust Berth Scheduling Using Machine Learning for Vessel Arrival Time Prediction - refined dataset

The refined dataset consists of edited data from raw AIS data. The data is organised as follows: There is one csv file per cargo ship (271 files in total from 1.csv to 271.csv). This file contains all calls of the respective ship at the Port of Miami for the given period from 2018 to 2020. To anonymize the data, the identifying ship data, i.e. the MMSI, was removed. Further information can be found in the paper in Section 3.1. (paper is under review and will be linked here as soon as available) The raw AIS data which are used are available on the websites of the National Oceanic and Atmospheric Administration (NOAA) Office for Coastal Management. An overview is published here: https://marinecadastre.gov/ais/本精炼数据集源自对原始自动识别系统（Automatic Identification System, AIS）数据的编辑处理。该数据集的组织形式如下：每艘货轮对应一个逗号分隔值（Comma-Separated Values, CSV）文件，共计271个文件，编号从1.csv至271.csv。每个文件均收录对应货轮在2018年至2020年指定时段内，停靠迈阿密港的全部航次记录。为完成数据匿名化处理，已移除船舶识别相关数据，即船舶移动业务识别码（Maritime Mobile Service Identity, MMSI）。更多详细信息可参阅论文的3.1章节（该论文目前处于审稿阶段，一经可用将立即在此处附上链接）。本数据集所使用的原始AIS数据，可从美国国家海洋和大气管理局（National Oceanic and Atmospheric Administration, NOAA）海岸管理办公室的官方网站获取。相关数据概览可通过以下链接查阅：https://marinecadastre.gov/ais/