AIMC Topic: Particulate Matter
Clear Filters Showing 11 to 20 of 196 articles
Spatiotemporal evolution and risk thresholds of PM components in China from the human health perspective.
Environmental pollution (Barking, Essex : 1987)
Apr 2, 2025
PM is a significant global public health hazard, with its components closely linked to various fatal diseases, thereby significantly increasing mortality rates. This study analysed the spatiotemporal evolution of PM-related mortality and death rates ...
Forecasting the concentration of the components of the particulate matter in Poland using neural networks.
Environmental science and pollution research international
Mar 21, 2025
Air pollution is a significant global challenge with profound impacts on human health and the environment. Elevated concentrations of various air pollutants contribute to numerous premature deaths each year. In Europe, and particularly in Poland, air...
PM concentration prediction using machine learning algorithms: an approach to virtual monitoring stations.
Scientific reports
Mar 8, 2025
One of the most important pollutants is PM, which is particularly important to monitor pollutant levels to keep the pollutant concentration under control. In this research, an attempt has been made to predict the concentrations of PM using four Machi...
PM concentration prediction using a whale optimization algorithm based hybrid deep learning model in Beijing, China.
Environmental pollution (Barking, Essex : 1987)
Mar 1, 2025
PM is a significant global atmospheric pollutant impacting visibility, climate, and public health. Accurate prediction of PM concentrations is critical for assessing air pollution risks and providing early warnings for effective management. This stud...
Prediction of school PM by an attention-based deep learning approach informed with data from nearby air quality monitoring stations.
Chemosphere
Feb 24, 2025
Predicting indoor air pollutants concentrations in schools is essential for ensuring a healthy learning environment. Traditional measurements methods pose challenges in cost, maintenance, and time. This study proposes a new approach using a deep lear...
High-resolution spatio-temporal estimation of street-level air pollution using mobile monitoring and machine learning.
Journal of environmental management
Feb 21, 2025
High spatio-temporal resolution street-level air pollution (SLAP) estimation is essential for urban air quality management, yet traditional methods face significant challenges in capturing the detailed spatial and temporal variability of pollution. M...
A study on the impact of meteorological and emission factors on PM concentrations based on machine learning.
Journal of environmental management
Feb 15, 2025
PM pollution, a major environmental and health concern, is influenced by a complex interplay of emission sources and meteorological conditions. Accurately identifying these factors and their contributions is essential for effective pollution manageme...
Enhancing PM2.5 prediction by mitigating annual data drift using wrapped loss and neural networks.
PloS one
Feb 11, 2025
In many deep learning tasks, it is assumed that the data used in the training process is sampled from the same distribution. However, this may not be accurate for data collected from different contexts or during different periods. For instance, the t...
A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors.
Sensors (Basel, Switzerland)
Feb 9, 2025
Accurate air pollution monitoring is critical to understand and mitigate the impacts of air pollution on human health and ecosystems. Due to the limited number and geographical coverage of advanced, highly accurate sensors monitoring air pollutants, ...
Combining deep learning and machine learning techniques to track air pollution in relation to vegetation cover utilizing remotely sensed data.
Journal of environmental management
Feb 5, 2025
The rapid urban expansion in Dhaka, the capital of Bangladesh, has escalated air pollution levels and led to a significant decrease in green spaces. This study employed machine learning (ML) and deep learning (DL) techniques to examine the relationsh...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823