Enhancing global maritime traffic network forecasting with gravity-inspired deep learning models
Aquatic non-indigenous species (NIS) pose significant threats to biodiversity, disrupting
ecosystems and inflicting substantial economic damages across agriculture, forestry, and …
ecosystems and inflicting substantial economic damages across agriculture, forestry, and …
Unfolding ais transmission behavior for vessel movement modeling on noisy data leveraging machine learning
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 …
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 …
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
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 …
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
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 …
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 …
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
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 …
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.
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 …
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 …
out. One of the current improvements that has been implemented is the possibility of …
A data mining approach for analysing globalshipping patterns.
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 …
unresolved problem is how to best operate fleets, given a sudden increase in demand, such …