Enhancing global maritime traffic network forecasting with gravity-inspired deep learning models

R Song, G Spadon, R Pelot, S Matwin, A Soares - Scientific reports, 2024 - nature.com
Aquatic non-indigenous species (NIS) pose significant threats to biodiversity, disrupting
ecosystems and inflicting substantial economic damages across agriculture, forestry, and …

Unfolding ais transmission behavior for vessel movement modeling on noisy data leveraging machine learning

G Spadon, MD Ferreira, A Soares, S Matwin - IEEE Access, 2022 - ieeexplore.ieee.org
The oceans are a source of an impressive mixture of complex data that could be used to
uncover relationships yet to be discovered. Such data comes from the oceans and their …

Cruise shipping network of ports in and around the emission control areas: a network structure perspective

M Kanrak, Y Lau, X Ling, S Traiyarach - Maritime Business Review, 2023 - emerald.com
Purpose The rapid growth in cruise shipping coupled with increasing public awareness of
climate change has led to increasing concerns about the impact cruise shipping poses on …

[PDF][PDF] Discovering gateway ports in maritime using temporal graph neural network port classification

D Altan, M Etemad, D Marijan… - arXiv preprint arXiv …, 2022 - assets.pubpub.org
Vessel navigation is influenced by various factors, such as dynamic environmental factors
that change over time or static features such as vessel type or depth of the ocean. These …

Gravity-Informed Deep Learning Framework for Predicting Ship Traffic Flow and Invasion Risk of Non-Indigenous Species via Ballast Water Discharge

R Song, G Spadon, S Bailey, R Pelot, S Matwin… - arXiv preprint arXiv …, 2024 - arxiv.org
Invasive species in water bodies pose a major threat to the environment and biodiversity
globally. Due to increased transportation and trade, non-native species have been …

An Active Learning Framework with a Class Balancing Strategy for Time Series Classification

S Das - arXiv preprint arXiv:2405.12122, 2024 - arxiv.org
Training machine learning models for classification tasks often requires labeling numerous
samples, which is costly and time-consuming, especially in time series analysis. This …

ImPORTance--Machine Learning-Driven Analysis of Global Port Significance and Network Dynamics for Improved Operational Efficiency

E Carlini, D Di Gangi, VM de Lira, H Kavalionak… - arXiv preprint arXiv …, 2024 - arxiv.org
Seaports play a crucial role in the global economy, and researchers have sought to
understand their significance through various studies. In this paper, we aim to explore the …

[PDF][PDF] Detecting the Spatiotemporal Characteristics of the Supply-chain Disruption and Estimating its Short Term Effects.

G Spiliopoulos, C Ducruet, LM Millefiori, P Braca… - EDBT/ICDT …, 2024 - ceur-ws.org
Ships are often considered as the backbone of the global economy. A fundamental
unresolved problem is how to best operate fleets, given a sudden increase in demand, such …

Positioning System for Fishing Fleets' Tracking and Assistance

Á Herrero-Martínez, MA Gutiérrez, A Ortega-Piris… - Fishes, 2023 - mdpi.com
The safety of people working at sea is a subject on which many studies have been carried
out. One of the current improvements that has been implemented is the possibility of …

A data mining approach for analysing globalshipping patterns.

G Spiliopoulos, C Ducruet, LM Millefiori, P Braca… - 2024 - researchsquare.com
Ships are often considered as the backbone of the global economy. A fundamental
unresolved problem is how to best operate fleets, given a sudden increase in demand, such …