首页> 外文会议>International Conference on Advanced Computational Intelligence >Application of machine learning methods in maritime safety information classification
【24h】

Application of machine learning methods in maritime safety information classification

机译:机床学习方法在海上安全信息分类中的应用

获取原文

摘要

In order to ensure the safety of maritime navigation, International Maritime Organization (IMO) developed the Global Maritime Distress and Safety System (GMDSS), which includes an important Maritime Safety Information (MSI) Broadcasting System that can broadcast navigational warnings and other crucial information. However, in most sea areas, the broadcast messages are still not pre-classified. Seafarers need to identify the theme of those received messages artificially, with low efficiency and accuracy. To solve this problem, several machine-learning based solutions are presented, implemented, and compared. Thousands of Navigational Telex (NAVTEX) messages, from 2011 to 2017, are used in the training and evaluation progress. The classifiers are compared in terms of accuracy, efficiency, precision and recall rate, and F-Measure respectively; and one of them is chosen as the optimal classifier. The chosen classifier performs well on solving the NAVTEX classification problem, and may further be used in other similar problems.
机译:为了确保海事导航的安全,国际海事组织(IMO)制定了全球海上遇险和安全系统(GMDSS),其中包括一个重要的海上安全信息(MSI)广播系统,可以广播导航警告和其他至关重要的信息。但是,在大多数海域,广播消息仍未预先分类。海员需要在效率和准确性下方人工中识别那些收到的消息的主题。为了解决这个问题,呈现了几种基于机器学习的解决方案,实现,并进行了比较。从2011年到2017年,数以千计的导航电传(Navtex)消息用于培训和评估进度。分类器分别在精度,效率,精度和召回率和F测量方面进行比较;其中一个被选为最佳分类器。所选择的分类器在解决Navtex分类问题时执行良好,并且可以进一步用于其他类似问题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号