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Recent Developments and Knowledge in Intelligent and Safe Marine Navigation

The maritime shipping sector toward intelligent and safe navigation is intrinsically tied to the integration of cutting-edge technologies (i.e., AI and big data). These technologies are being harnessed across multiple facets of the maritime domain. It is evident that these methodologies have the pot...

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Format: Online
Sprog:engelsk
Udgivet: MDPI - Multidisciplinary Digital Publishing Institute 2024
Fag:
nonlinear-fitting redundant sliding mode
event-triggered
abnormal input
neural network
artificial intelligence transportation robots
track tracking
unmanned surface vehicles
deep reinforcement learning
autonomous collision avoidance
COLREGs
non-linear Nomoto model
parameter identification
multi-innovation least-squares
support vector regression
ship routing
artificial neural network
speed configuration
A* algorithm
traffic safety
offshore wind farms
YOLOv7
stereo vision
deep learning
collision avoidance
improved artificial potential field
nonlinear model predictive control
ship maneuverability
maritime traffic safety
maritime accident
Bayesian network (BN)
accident scenario analysis
Netica
contour extraction
object detection
semantic segmentation
coordinate mapping
risk assessment
maritime transport
fault tree analysis
Bayesian network
Liquid Natural Gas (LNG)
ship knowledge graph
illegal behavior
fake ship license plates
decision-making
traffic management
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
Online adgang:ONIX_20240514_9783039286232_94
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Summary:The maritime shipping sector toward intelligent and safe navigation is intrinsically tied to the integration of cutting-edge technologies (i.e., AI and big data). These technologies are being harnessed across multiple facets of the maritime domain. It is evident that these methodologies have the potential to significantly enhance the intelligence and safety of ships. This SI stands as a compendium of research papers that not only enrich the academic dialogue but also support substantial practical implications for the maritime industry. The insights and innovations contained within this SI are imperative in furthering the frontiers of intelligent and safe navigation. The contributions encompass a spectrum of recent developments, encompassing topics such as big data fusion for ship detection, collision avoidance through deep reinforcement learning approaches, and ship system identification, route planning, etc. These methods draw from a confluence of expertise, merging insights from ship science, AI, and their interdisciplinary interactions. Collectively, the research presented in this SI constitutes a vital stride in the ongoing endeavor to fortify and refine intelligent navigation.

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