AI Medical Compendium Topic:
Environmental Monitoring

Clear Filters Showing 441 to 450 of 998 articles

Marine oil spill detection and segmentation in SAR data with two steps Deep Learning framework.

Marine pollution bulletin
Marine oil spills pose significant ecological and economic threats worldwide, requiring effective decision-making tools. In this study, the optimal parameters, and configurations for Deep Learning models in oil spill classification and segmentation u...

Assessing the risk of E. coli contamination from manure application in Chinese farmland by integrating machine learning and Phydrus.

Environmental pollution (Barking, Essex : 1987)
This study aims to present a comprehensive study on the risks associated with the residual presence and transport of Escherichia coli (E. coli) in soil following the application of livestock manure in Chinese farmlands by integrating machine learning...

Coastal ozone dynamics and formation regime in Eastern China: Integrating trend decomposition and machine learning techniques.

Journal of environmental sciences (China)
Machine-learning is a robust technique for understanding pollution characteristics of surface ozone, which are at high levels in urban China. This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to i...

Evaluation of mine ecological environment based on fuzzy hierarchical analysis and grey relational degree.

Environmental research
In order to improve the level of mine ecological environment management and restoration, and to improve and enhance the overall environmental quality of mines. This study takes coal mine as the perspective, and constructs evaluation indexes in two st...

An Integrated Smart Pond Water Quality Monitoring and Fish Farming Recommendation Aquabot System.

Sensors (Basel, Switzerland)
The integration of cutting-edge technologies such as the Internet of Things (IoT), robotics, and machine learning (ML) has the potential to significantly enhance the productivity and profitability of traditional fish farming. Farmers using traditiona...

Urban environmental monitoring and health risk assessment introducing a fuzzy intelligent computing model.

Frontiers in public health
INTRODUCTION: To enhance the precision of evaluating the impact of urban environments on resident health, this study introduces a novel fuzzy intelligent computing model designed to address health risk concerns using multi-media environmental monitor...

The consistent fuzzy suitability assessment of forest land resources with multi-source heterogeneous data.

Environmental monitoring and assessment
In view of the suitability assessment of forest land resources, a consistent fuzzy assessment method with heterogeneous information is proposed. Firstly, some formulas for transforming large-scale real data and interval data into fuzzy numbers are pr...

Environmental impact assessment of ocean energy converters using quantum machine learning.

Journal of environmental management
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...

Retrieval of subsurface dissolved oxygen from surface oceanic parameters based on machine learning.

Marine environmental research
Oceanic dissolved oxygen (DO) is crucial for oceanic material cycles and marine biological activities. However, obtaining subsurface DO values directly from satellite observations is limited due to the restricted observed depth. Therefore, it is esse...

Application of improved machine learning in large-scale investigation of plastic waste distribution in tourism Intensive artificial coastlines.

Environmental pollution (Barking, Essex : 1987)
Oceans are ultimately a sink of plastic waste. Complex artificial coastlines pose remarkable challenges for coastal plastic waste monitoring. With the development of machine learning methods, high detection accuracy can be achieved; however, many fal...