提升AIS数据完整性可显著改善分类准确率，保障海上安全与效率。
Data integrity vs. inference accuracy in large AIS datasets
- 分析大规模AIS数据完整性对分类精度的影响
- 实测显示数据质量提升可显著改善推断效果
- 适合关注海上交通监控与数据可信度的研究者
自动船舶识别系统（AIS）在监测海上交通中发挥关键作用，其数据是分析与决策的基础。数据完整性直接影响海上安全、交通管理与环境保护中的推断与决策正确性。本文研究大规模AIS数据中数据完整性对分类准确性的影响，提出误差检测与纠正方法及数据验证技术，以提升AIS系统的可靠性。实验结果表明，提升数据完整性能显著提高推断质量，直接促进海上作业效率与安全性。
原文摘要 · Abstract (English)
Automatic Ship Identification Systems (AIS) play a key role in monitoring maritime traffic, providing the data necessary for analysis and decision-making. The integrity of this data is fundamental to the correctness of infer-ence and decision-making in the context of maritime safety, traffic manage-ment and environmental protection. This paper analyzes the impact of data integrity in large AIS datasets, on classification accuracy. It also presents er-ror detection and correction methods and data verification techniques that can improve the reliability of AIS systems. The results show that improving the integrity of AIS data significantly improves the quality of inference, which has a direct impact on operational efficiency and safety at sea.
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