Artificial Intelligence for Air Quality Monitoring and Prediction
portes grátis
Artificial Intelligence for Air Quality Monitoring and Prediction
Dhiman, Gaurav; Awasthi, Amit; Charan Pattnayak, Kanhu; Raj Tiwari, Pushp
Taylor & Francis Ltd
10/2024
301
Dura
9781032683799
Pré-lançamento - envio 15 a 20 dias após a sua edição
Descrição não disponível.
1. Air Quality Monitoring (AQM) and Prediction: Transitioning from Conventional to AI Techniques. 2. Temporal Variations of Sulphur Dioxide Levels across India: A Biennial Assessment (2020-2021). 3. The Effectiveness of Machine Learning Techniques in Enhancing Air Quality Prediction. 4. Enhancing Environmental Resilience: Precision in Air Quality Monitoring through AI-Driven Real-Time Systems. 5. Forecasting Air Pollution with Artificial Intelligence: Recent Advancements at Global Scale and Future Perspectives. 6. Integrating AI into Air Quality Monitoring: Precision and Progress. 7. Application of AI-based Tools in Air Pollution Study. 8. Study of Extreme Weather Events in the Central Himalayan Region through Machine Learning and Artificial Intelligence: A Case Study. 9. Machine Learning Applications in Air Quality Management and Policies. 10. A Glimpse into Tomorrow's Air: Leveraging PM 2.5 with FP Prophet as a Forecasting Model. 11. Air Quality Forecast using Machine Learning Algorithms. 12. Deep Learning Approaches in Air Quality Prediction. 13. Incorporation of AI with Conventional Monitoring Systems. 14. A Comparative Evaluation of AI-Based Methods and Traditional Approaches for Air Quality Monitoring: Analyzing Pros and Cons. 15. ML Driven Hydrogen Yield Prediction for Sustainable Environment.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Atmosphere, Climate, Weather Patterns, Meteorology;Environment, Air Pollution, Monitoring;Machine learning, Deep learning, Prediction;Data Analysis, Data Mining, Statistical Modeling;Air Pollution Control, Emission Reduction, Treatment Technologies;Satellite Observations, Image Processing, Environmental Monitoring. GIS
1. Air Quality Monitoring (AQM) and Prediction: Transitioning from Conventional to AI Techniques. 2. Temporal Variations of Sulphur Dioxide Levels across India: A Biennial Assessment (2020-2021). 3. The Effectiveness of Machine Learning Techniques in Enhancing Air Quality Prediction. 4. Enhancing Environmental Resilience: Precision in Air Quality Monitoring through AI-Driven Real-Time Systems. 5. Forecasting Air Pollution with Artificial Intelligence: Recent Advancements at Global Scale and Future Perspectives. 6. Integrating AI into Air Quality Monitoring: Precision and Progress. 7. Application of AI-based Tools in Air Pollution Study. 8. Study of Extreme Weather Events in the Central Himalayan Region through Machine Learning and Artificial Intelligence: A Case Study. 9. Machine Learning Applications in Air Quality Management and Policies. 10. A Glimpse into Tomorrow's Air: Leveraging PM 2.5 with FP Prophet as a Forecasting Model. 11. Air Quality Forecast using Machine Learning Algorithms. 12. Deep Learning Approaches in Air Quality Prediction. 13. Incorporation of AI with Conventional Monitoring Systems. 14. A Comparative Evaluation of AI-Based Methods and Traditional Approaches for Air Quality Monitoring: Analyzing Pros and Cons. 15. ML Driven Hydrogen Yield Prediction for Sustainable Environment.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Atmosphere, Climate, Weather Patterns, Meteorology;Environment, Air Pollution, Monitoring;Machine learning, Deep learning, Prediction;Data Analysis, Data Mining, Statistical Modeling;Air Pollution Control, Emission Reduction, Treatment Technologies;Satellite Observations, Image Processing, Environmental Monitoring. GIS
