AI Medical Compendium Journal:
Marine pollution bulletin

Showing 21 to 30 of 64 articles

Hypoxia extreme events in a changing climate: Machine learning methods and deterministic simulations for future scenarios development in the Venice Lagoon.

Marine pollution bulletin
Climate change pressures include the dissolved oxygen decline that in lagoon ecosystems can lead to hypoxia, i.e. low dissolved oxygen concentrations, which have consequences to ecosystem functioning including biogeochemical cycling from mild to seve...

Enhancing shipboard oil pollution prevention: Machine learning innovations in oil discharge monitoring equipment.

Marine pollution bulletin
Maritime operations face significant challenges in environmental stewardship, particularly in managing oil discharges from tankers as mandated by the International Convention for the Prevention of Pollution from Ships (MARPOL) Annex I, Regulation 34....

Comparison of conventional and machine learning regression models for accurate prediction of selected optical active components - A case study: The Gulf of Izmit.

Marine pollution bulletin
This study hypothesizes that advanced machine learning (ML) models can more accurately predict certain critical water quality parameters in marine environments compared to conventional regression techniques. We specifically evaluated the spatio-tempo...

Efficient plastic detection in coastal areas with selected spectral bands.

Marine pollution bulletin
Marine plastic pollution poses significant ecological, economic, and social challenges, necessitating innovative detection, management, and mitigation solutions. Spectral imaging and optical remote sensing have proven valuable tools in detecting and ...

Towards reliable data: Validation of a machine learning-based approach for microplastics analysis in marine organisms using Nile red staining.

Marine pollution bulletin
Microplastic (MP) research faces challenges due to costly, time-consuming, and error-prone analysis techniques. Additionally, the variability in data quality across studies limits their comparability. This study addresses the critical need for reliab...

Utilizing deep learning algorithms for automated oil spill detection in medium resolution optical imagery.

Marine pollution bulletin
This study evaluates the performance of three typical convolutional neural network based deep learning algorithms for oil spill detection using medium-resolution optical satellite imagery from Sentinel-2 MSI, Landsat-8 OLI, and Landsat-9 OLI2. Oil sl...

An update for various applications of Artificial Intelligence (AI) for detection and identification of marine environmental pollutions: A bibliometric analysis and systematic review.

Marine pollution bulletin
Marine environmental pollution is one of the growing concerns of humans all over the world. Therefore, managing these marine pollutants has been a crucial matter for scientists in recent decades. Thus, researchers have tried to implement artificial i...

Enhancing water quality monitoring through the integration of deep learning neural networks and fuzzy method.

Marine pollution bulletin
The escalating growth of the global population has led to degraded water quality, particularly in seawater environments. Water quality monitoring is crucial to understanding the dynamic changes and implementing effective management strategies. In thi...

Enhancing microalgae classification accuracy in marine ecosystems through convolutional neural networks and support vector machines.

Marine pollution bulletin
Accurately classifying microalgae species is vital for monitoring marine ecosystems and managing the emergence of marine mucilage, which is crucial for monitoring mucilage phenomena in marine environments. Traditional methods have been inadequate due...

Assessment of groundwater quality in arid regions utilizing principal component analysis, GIS, and machine learning techniques.

Marine pollution bulletin
Assessing water quality in arid regions is vital due to scarce resources, impacting health and sustainable management.This study examines groundwater quality in Assuit Governorate, Egypt, using Principal Component Analysis, GIS, and Machine Learning ...