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A Deep-Learning-Based Visualization Tool for Air Pollution Forecasting
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DOI：10.1109/MS.2024.3496663.png)
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Abstract
En 中文
This article presents a comprehensive visualization tool that integrates real-time observation and sensing data with various forecasting models, including numerical and deep-learning approaches. The developed software framework efficiently manages data flow, configures forecasting models, and visualizes monitoring and prediction information.
Keywords:
Atmospheric modeling
Predictive models
Data models
Numerical models
Forecasting
Data visualization
Real-time systems
Training
Servers
Monitoring