AIMC Topic: Oceans and Seas

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Little-to-no industrial fishing occurs in fully and highly protected marine areas.

Science (New York, N.Y.) Jul 24, 2025
There is a widespread perception that illegal fishing is common in marine protected areas (MPAs) due to strong incentives for poaching and the high cost of monitoring and enforcement. Using artificial intelligence and satellite-based Earth observatio...
Artificial Intelligence Conservation of Natural Resources Oceans and Seas Fisheries Animals Fishes
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Harmful Algae Forecasting through an Ocean Data Justice Lens.

Environmental science & technology Jun 10, 2025
Forecasting systems for harmful algal blooms (HABs) are becoming more common, as HAB monitoring is increasingly networked and aggregated at national and global scales. Ocean forecasting programs in other fields have had unintended consequences and ou...
Oceans and Seas Biodiversity Forecasting Harmful Algal Bloom Environmental Monitoring
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Prediction of anthropogenic I in the South China Sea based on machine learning.

Journal of environmental radioactivity May 2, 2025
With the rapid increase in the number of nuclear power plants along the China coast and the potential for releases of radioactive substances to marine ecosystems, it is important to investigate and predict the dispersion of radionuclides in the seas ...
Machine Learning Radiation Monitoring Support Vector Machine Water Pollutants, Radioactive Iodine Radioisotopes China Seawater Oceans and Seas
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Machine learning to identify environmental drivers of phytoplankton blooms in the Southern Baltic Sea.

Scientific reports Jan 24, 2025
Phytoplankton blooms exhibit varying patterns in timing and number of peaks within ecosystems. These differences in blooming patterns are partly explained by phytoplankton:nutrient interactions and external factors such as temperature, salinity and l...
Oceans and Seas Ecosystem Eutrophication Salinity Chlorophyll Phytoplankton Machine Learning Temperature
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The abiologically and biologically driving effects on organic matter in marginal seas revealed by deep learning-assisted model analysis.

The Science of the total environment Jan 3, 2025
The biogeochemical processes of organic matter exhibit notable variability and unpredictability in marginal seas. In this study, the abiologically and biologically driving effects on particulate organic matter (POM) and dissolved organic matter (DOM)...
China Organic Chemicals Environmental Monitoring Deep Learning Seawater Oceans and Seas Humic Substances Water Pollutants, Chemical Particulate Matter
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Modeling the global ocean distribution of dissolved cadmium based on machine learning-SHAP algorithm.

The Science of the total environment Dec 12, 2024
Cadmium (Cd) is a bio-essential trace metal in the ocean that can be toxic at high concentrations, significantly impacting the marine environment and phytoplankton growth. Its distribution pattern is closely proportional to that of phosphate (PO), al...
Seawater Oceans and Seas Algorithms Environmental Monitoring Models, Chemical Cadmium Water Pollutants, Chemical Machine Learning
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Protocol for developing an explosion-propeller hybrid driving underwater robot for AI-based concrete overhaul in real marine environments.

STAR protocols Sep 23, 2024
We recently developed an explosion-propeller hybrid driving underwater robot combined with an AI-based concrete damage detection technique for concrete overhaul in real marine environments. Here, we describe steps for establishing a detection dataset...
Oceans and Seas Explosions Algorithms Construction Materials Robotics Artificial Intelligence
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Fish-inspired tracking of underwater turbulent plumes.

Bioinspiration & biomimetics Sep 3, 2024
Autonomous ocean-exploring vehicles have begun to take advantage of onboard sensor measurements of water properties such as salinity and temperature to locate oceanic features in real time. Such targeted sampling strategies enable more rapid study of...
Animals Algorithms Water Movements Swimming Robotics Computer Simulation Oceans and Seas Fishes Equipment Design Hydrodynamics Biomimetics
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Forecasting of compound ocean-fluvial floods using machine learning.

Journal of environmental management Jun 13, 2024
Flood modelling and forecasting can enhance our understanding of flood mechanisms and facilitate effective management of flood risk. Conventional flood hazard and risk assessments usually consider one driver at a time, whether it is ocean, fluvial or...
Support Vector Machine Forecasting Oceans and Seas Neural Networks, Computer Floods Models, Theoretical Machine Learning Rivers
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Environmental impact assessment of ocean energy converters using quantum machine learning.

Journal of environmental management Jun 4, 2024
The depletion of fossil energy reserves and the environmental pollution caused by these sources highlight the need to harness renewable energy sources from the oceans, such as waves and tides, due to their high potential. On the other hand, the large...
Environmental Monitoring Machine Learning Algorithms Renewable Energy Environment Ecosystem Oceans and Seas
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