Air Quality Index (AQI) Prediction in Holy Makkah Based on Machine Learning Methods
importance 5/10
ai assisted
Air Quality Monitoring and Forecasting air quality management stage: research
Problem
Predicting air quality index levels in Makkah is hard due to variable spatiotemporal pollution, especially with millions of Hajj and Ramadan visitors.
Why it matters
Air pollution management in Makkah affects millions of visitors each year.
What the AI did
Fine decision tree, ensemble boosted tree and ensemble bagged tree models were trained on 2016-2018 Makkah air quality data to forecast AQI levels.
Results
EBOT achieved 97.4% accuracy, correctly predicting 75 of 77 samples
Impact
Demonstrated ML-based AQI forecasting for the Makkah region on 2016-2018 data.
Record
| Venue | Sustainability |
|---|---|
| Published | 2023 |
| Work type | article |
| Authors | Abdulrazak H. Almaliki, Abdessamed Derdour, Enas Ali |
| Citations | 25 (OpenAlex, at import time) |
| References | 27 |
| Model or method | FDT, EBOT, EBAT (decision tree ensembles) |
| Organization | not stated in source |
| Primary source | https://doi.org/10.3390/su151713168 |
| Open access | gold |
| Keywords | air quality index, machine learning, Makkah, ensemble trees, forecasting |
Importance rating
5
real but narrower advance
Abstract states Makkah draws millions of visitors during Hajj and Ramadan, making air quality management consequential; demonstrated only on 2016-2018 regional data with 77 samples.
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