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Conference Paper
Hybrid Deep Learning-Based Air and Water Quality Prediction Model
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- Authors
- Jungeun Yoon, Dasong Yu, Youngjae Lee
- Issue Date
- 2023-10
- Citation
- European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) 2023, pp.665-670
- Language
- English
- Type
- Conference Paper
- Abstract
- This paper analyzes the impact of surrounding data on predicting air and water pollution levels by incorporating relevant features and examining their influence. By doing so, we can confirm the relationship between air and water pollution. A hybrid deep learning-based model is trained and various datasets and models are compared and analyzed. The proposed GCN-GRU model achieved the best results not only for PM2.5 but also for Dissolved Oxygen. The hybrid model takes into account the spatial and temporal effects of data characteristics and provides more accurate environmental prediction information through correlation analysis.