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Data/Knowledge-Driven Behaviour Analysis for Maritime Autonomous Surface Ships

Maritime traffic data (e.g., radar data, AIS data, and CCTV data) provide designers, officers on watch, and traffic operators with extensive information about the states of ships at present and in history, representing a treasure trove for behavior analysis. Additionally, navigation rules and regula...

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Bibliographic Details
Main Author: Wen, Yuanqiao
Other Authors: Hahn, Axel, Valdez Banda, Osiris, Huang, Yamin
Format: eBook
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
Complex Waters
Transport Technology And Trades / Bicssc
Velocity Obstacle
Ais
Intelligent Decision-making
Ais Data
Ship Behavior
Regularization-trajectory Cell
N/a
Colregs
Mixed Waterborne Traffic
Deep Learning
Hazard Identification
Ship Object
Maritime Safety
Effects Of Wind And Current
Cognitive Space
Ship Domain
Inland Waterway Transportation
History Of Engineering And Technology / Bicssc
Collision Alert System (cas)
Ship Traffic Flow
Unmanned Surface Vehicle
Unmanned Surface Vehicle (usv)
Available Maneuvering Margins (amm)
Technology: General Issues / Bicssc
Yolo
Autonomous Ship
Motion Planning
Information Perception
Intersection
Risk Assessment
Multi-sensor
Obstacles Classification
Collision Avoidance
Ontology
Clustering
Deep Convolutional Neural Network
Ship Autonomy
Spatiotemporal Dependence
Morphological Operation
Ship Manoeuvrability
Multi-scale Analysis
Execution
Semantic Modeling
Ship Exhaust Behavior
Formal Expression
Gate Recurrent Unit
Trajectory Classification
Ransac
Preliminary Hazard Analysis
Maritime Autonomous Surface Ships
Ship Stability
Detection And Tracking
Bayesian Framework
Fuzzy Rules
Hybrid Causal Logic
Ship Intention Identification
Deduction Of The Manoeuvring Process
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:Maritime traffic data (e.g., radar data, AIS data, and CCTV data) provide designers, officers on watch, and traffic operators with extensive information about the states of ships at present and in history, representing a treasure trove for behavior analysis. Additionally, navigation rules and regulations (i.e., knowledge) offer valuable prior knowledge about ship manners at sea. Combining multisource heterogeneous big data and artificial intelligence techniques inspires innovative and important means for the development of MASS. This reprint collects twelve contributions published in "Data-/Knowledge-Driven Behavior Analysis of Maritime Autonomous Surface Ships" Special Issue during 2021-2022, aiming to provide new views on data-/knowledge-driven analytical tools for maritime autonomous surface ships, including data-driven behavior modeling, knowledge-driven behavior modeling, multisource heterogeneous traffic data fusion, risk analysis and management of MASS, etc.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (262 p.)
ISBN:9783036574424
books978-3-0365-7442-4
9783036574431

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