船舶航行状态辨识实验数据

本数据为船舶航行状态辨识实验数据，主要用于项目指标7.1-面向多式联运全息生态链的多式联运智能调度集成系统数据底盘中相关理论模型构建和技术研发。本数据以数据库文件的形式存储，存储格式为sql，数据生成时间为2019年1月，本数据是一种中间结果数据，是在船舶轨迹数据的基础上，通过构建模型，准确辨识船舶在每个时刻所处的航行状态。项目组以DBSCAN密度聚类模型为基础，提出了一种前向搜索算法，结合航速、航速变化率、航向和航向变化率等参数实现对船舶航行状态的精准辨识。本数据包含8个sql文件，每个数据文件对应一条用于算法开发的船舶轨迹，8个文件一共8条船舶，每个文件字段格式保持一致。This dataset is experimental data for ship navigation state identification, primarily intended for the construction of relevant theoretical models and technological R&D under Project Indicator 7.1: Data Chassis of the Multimodal Transport Intelligent Scheduling Integrated System Oriented towards the Holographic Ecosystem of Multimodal Transport. Stored in the form of database files with SQL as the storage format, this dataset was generated in January 2019. It is a type of intermediate result data derived by accurately identifying the navigation state of the ship at each moment via model construction based on original ship trajectory data. The project team proposed a forward search algorithm based on the DBSCAN density clustering model, and achieved accurate identification of ship navigation states by combining parameters such as ship speed, speed change rate, course, and course change rate. This dataset comprises 8 SQL files, each corresponding to one ship trajectory for algorithm development, totaling 8 ships across all 8 files, and all files share consistent field formats.

搜集汇总

背景与挑战

背景概述

该数据集为船舶航行状态辨识实验数据，以SQL数据库文件形式存储，包含8个文件对应8条船舶轨迹，数据基于DBSCAN密度聚类模型和前向搜索算法生成，用于多式联运智能调度系统相关研发。数据生成于2019年1月，总大小为1.29MB，由大连海事大学创建并发布。