AIMC Topic: Atmosphere

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Development of an automated photolysis rates prediction system based on machine learning.

Journal of environmental sciences (China) May 1, 2025
Based on observed meteorological elements, photolysis rates (J-values) and pollutant concentrations, an automated J-values predicting system by machine learning (J-ML) has been developed to reproduce and predict the J-values of OD, NO, HONO, HO, HCHO...
Machine Learning China Environmental Monitoring Air Pollutants Ozone Models, Chemical Photolysis Aerosols Atmosphere
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Rapid fiber-detection technique by artificial intelligence in phase-contrast microscope images of simulated atmospheric samples.

Annals of work exposures and health Apr 22, 2024
Since the manufacture, import, and use of asbestos products have been completely abolished in Japan, the main cause of asbestos emissions into the atmosphere is the demolition and removal of buildings built with asbestos-containing materials. To dete...
Humans Neural Networks, Computer Artificial Intelligence Environmental Monitoring Japan Atmosphere Microscopy, Phase-Contrast Asbestos Asbestos, Serpentine
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Development of rapid and highly accurate method to measure concentration of fibers in atmosphere using artificial intelligence and scanning electron microscopy.

Journal of occupational health Jan 1, 2021
AIM: We aimed to develop a measurement method that can count fibers rapidly by scanning electron microscopy equipped with an artificial intelligence image recognition system (AI-SEM), detecting thin fibers which cannot be observed by a conventional p...
Humans Artificial Intelligence Occupational Exposure Particulate Matter Image Interpretation, Computer-Assisted Microscopy, Electron, Scanning Atmosphere Air Pollutants, Occupational Air Filters Asbestos
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Bayesian framework for simulation of dynamical systems from multidimensional data using recurrent neural network.

Chaos (Woodbury, N.Y.) Dec 1, 2019
We suggest a new method for building data-driven dynamical models from observed multidimensional time series. The method is based on a recurrent neural network with specific structure, which allows for the joint reconstruction of both a low-dimension...
Neural Networks, Computer Data Analysis Algorithms Computer Simulation Models, Theoretical Bayes Theorem Signal Processing, Computer-Assisted Probability Stochastic Processes Atmosphere
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How AI and satellites could help predict volcanic eruptions.

Nature Mar 1, 2019
Humans Neural Networks, Computer Artificial Intelligence Machine Learning Forecasting Environmental Monitoring Satellite Communications Geographic Mapping Atmosphere Volcanic Eruptions
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