On the public citation graph

ssrn.4506775

0 signed · 17 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00773-014-0293-yopenalex-extracted

Introduction of MMG standard method for ship maneuvering predictions

inferredcites →https://doi.org/10.1016/j.oceaneng.2017.04.008openalex-extracted

An integrated empirical manoeuvring model for inland vessels

inferredcites →https://doi.org/10.1016/j.oceaneng.2020.107922openalex-extracted

Ship collision avoidance anthropomorphic decision-making for structured learning based on AIS with Seq-CGAN

inferredcites →https://doi.org/10.1016/j.oceaneng.2021.109612openalex-extracted

Multi-ship encounter situation adaptive understanding by individual navigation intention inference

inferredcites →https://doi.org/10.1016/j.oceaneng.2022.111309openalex-extracted

Automatic traffic scenarios generation for autonomous ships collision avoidance system testing

inferredcites →https://doi.org/10.1016/j.oceaneng.2022.112777openalex-extracted

Anticipation of ship behaviours in multi-vessel scenarios

inferredcites →https://doi.org/10.1016/j.ssci.2019.09.018openalex-extracted

Ship collision avoidance methods: State-of-the-art

inferredcites →https://doi.org/10.1016/j.ssci.2020.104798openalex-extracted

Preventing shipping accidents: Past, present, and future of waterway risk management with Baltic Sea focus

inferredcites →https://doi.org/10.1016/j.ssci.2020.104799openalex-extracted

Towards simulation-based verification of autonomous navigation systems

inferredcites →https://doi.org/10.1109/itsc.2015.164openalex-extracted

Defining and Substantiating the Terms Scene, Situation, and Scenario for Automated Driving

inferredcites →https://doi.org/10.1177/1748006x211051829openalex-extracted

A novel risk assessment process: Application to an autonomous inland waterways ship

inferredcites →https://doi.org/10.1177/1748006x211069277openalex-extracted

Automatic simulation-based testing of autonomous ships using Gaussian processes and temporal logic

inferredcites →https://doi.org/10.3233/isp-1981-2832103openalex-extracted

Hydrodynamic derivatives on ship manoeuvring

inferredcites →https://doi.org/10.3390/jmse10101460openalex-extracted

Inland Waterway Ship Path Planning Based on Improved RRT Algorithm

inferredcites →https://doi.org/10.3390/jmse10101536openalex-extracted

Multi-Ship Encounter Situation Identification and Analysis Based on AIS Data and Graph Complex Network Theory

inferredcites →https://doi.org/10.3390/jmse11040830openalex-extracted

Ship Autonomous Collision-Avoidance Strategies—A Comprehensive Review

inferredcites →https://doi.org/10.3390/su13158162openalex-extracted

Modeling Vessel Behaviours by Clustering AIS Data Using Optimized DBSCAN

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.