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Updated: Jul 6, 2026

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提高海上安全:使用深度学习模型与轨迹预测边界估计碰撞概率

Robertas Jurkus1, Julius Venskus2, Jurgita Markevičiūtė2

  • 1Institute of Data Science and Digital Technologies, Vilnius University, 01513 Vilnius, Lithuania.

Sensors (Basel, Switzerland)
|March 17, 2025
PubMed
概括

这项研究使用深度学习来预测船舶路径,并评估在博恩霍尔姆岛附近的碰撞风险. 合规预测区域 (CPR) 可靠地预测海上碰撞风险,提高航行安全.

关键词:
碰撞风险评分 碰撞风险评分符合性预测区域的区域.长期短期记忆 长期短期记忆不确定性量化不确定性量化船舶碰撞探测器船只碰撞探测器预测船只轨迹的边界.

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Real-World Applications of Space Curves01:29

Real-World Applications of Space Curves

Modern aerospace navigation depends on the accurate prediction of motion in three-dimensional space. In defense applications, radar systems continuously track both interceptors and moving aerial targets to find whether their flight paths will result in a collision. These motions are modeled mathematically as space curves, which represent paths that change continuously with time. Each object’s position is described by a vector function that specifies its location in terms of time-dependent...