基于分布式区块链和联合强化学习的智能船舶交通监督系统,用于协作决策优化
Zhang Wei1, Pan Rongjun2, Wang Shijie2
1School of Maritime, Jiujiang Polytechnic University of Science and Technology, Jiujiang, 332020, China. gavin.teekay@gmail.com.
Scientific reports
|November 1, 2025
概括
本研究介绍了一种使用区块链和联合强化学习进行船舶交通监督的智能模型. 它增强了海上运营中的协作和决策,同时确保数据隐私和安全.
科学领域:
- 海事技术 在海事技术.
- 人工智能的人工智能
- 分布式系统 分布式系统
背景情况:
- 传统的海上交通监控面临着数据孤岛和隐私问题等挑战.
- 集中决策阻碍了海上监督的有效多管辖区协调.
- 缺乏安全的数据共享阻碍了海事当局之间的运营自主权.
研究的目的:
- 开发用于船舶交通协作监督的智能决策优化模型.
- 整合分布式区块链技术与联合强化学习,以加强海上交通管理.
- 解决传统系统中的数据孤岛,隐私问题和决策瓶问题.
主要方法:
- 多层架构包括数据,区块链,联合学习和决策层.
- 利用分布式区块链实现数据完整性,不变性和通过智能合约安全共享.
- 采用联合强化学习来保护隐私的协作模式培训.
主要成果:
- 实现了93.6%的决策准确度,520毫秒的平均响应时间和每秒285个交易吞吐量.
- 在紧急避免碰撞,识别异常行为和搜救方面表现出实际有效性.
- 报告说,事件响应时间减少了40%,跨机构协作效率提高了60%.
结论:
- 拟议的框架为下一代海上交通管理系统提供了坚实的基础.
- 区块链和联合强化学习的整合使得安全的多方合作成为可能.
- 该模型提供智能决策优化,同时保持运营自主性和数据隐私.
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