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Traffic Pattern Mining and Forecasting Technologies in Maritime Traffic Service Networks: A Comprehensive Survey

机译:海上交通服务网络中交通模式挖掘和预测技术:综合调查

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摘要

Maritime traffic service networks and information systems play a vital role in maritime traffic safety management. The data collected from the maritime traffic networks are essential for the perception of traffic dynamics and predictive traffic regulation. This paper is devoted to surveying the key processing components in maritime traffic networks. Specifically, the latest progress on maritime traffic data mining technologies for maritime traffic pattern extraction and the recent effort on vessels' motion forecasting for better situation awareness are reviewed. Through the review, we highlight that the traffic pattern knowledge presents valued insights for wide-spectrum domain application purposes, and serves as a prerequisite for the knowledge based forecasting techniques that are growing in popularity. The development of maritime traffic research in pattern mining and traffic forecasting reviewed in this paper affirms the importance of advanced maritime traffic studies and the great potential in maritime traffic safety and intelligence enhancement to accommodate the implementation of the Internet of Things, artificial intelligence technologies, and knowledge engineering and big data computing solution.
机译:海上交通服务网络和信息系统在海上交通安全管理中发挥着重要作用。从海上交通网络收集的数据对于交通动态和预测性交流的感知至关重要。本文致力于测量海上交通网络中的关键处理组件。具体而言,综述了海上交通数据采矿技术对海上交通数据采矿技术的最新进展,以及船舶运动预测的近期努力进行了综述。通过审查,我们强调了交通模式知识为广泛的频谱域应用目的提供了有价值的见解,并作为基于知识的预测技术的先决条件,这些技术正在越来越受欢迎。本文审查了模式挖掘和交通预测海上交通研究的发展肯定了先进的海上交通研究和海上交通安全和情报增强潜力的重要性,以适应事物互联网,人工智能技术和知识工程和大数据计算解决方案。

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