Bi-LSTM based Air Pollution Risk Likelihood Prognostication using Ensemble Approach
Author:
Affiliation:
1. University for Women,Indira Gandhi Delhi Technical,CoE-AI,Delhi,India
2. University for Women,Indira Gandhi Delhi Technical,AI&DS,Delhi,India
3. University for Women,Indira Gandhi Delhi Technical,VC,Delhi,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10048789/10048790/10048826.pdf?arnumber=10048826
Reference16 articles.
1. Artificial intelligence-enabled context-aware air quality prediction for smart cities
2. APPLICATION OF ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF AIR POLLUTION LEVELS IN ENVIRONMENTAL MONITORING
3. Application of Neuro-Fuzzy in Prediction of Air Pollution in Urban Areas
4. An Adaptive Kalman Filtering Approach to Sensing and Predicting Air Quality Index Values
5. Spatial prediction of air pollution levels using a hierarchical Bayesian spatiotemporal model in Catalonia, Spain
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