Machine learning for the assessment and mitigation of SMOG hazard in low-middle income developing countries
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| Natura: | Recurso digital |
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Zenodo
2024
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| _version_ | 1866901669191614464 |
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| author | Anjum, Sitara Rasheed, Rizwan Rashid Ahmed, Sajid Anjum, Sharoon Batool, Fizza |
| author_facet | Anjum, Sitara Rasheed, Rizwan Rashid Ahmed, Sajid Anjum, Sharoon Batool, Fizza |
| contents | <p><span>This is the first statistical research based on of five years of smog data from 2019 to 2023 in Lahore, using machine learning techniques. This research used machine learning techniques, namely using Python programming for data analysis. Python-based analyses can effectively assess regions with poor air quality and high pollution levels. This allows targeted interventions and restrictions to safeguard community health and avert respiratory disorders. </span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_14236194 |
| institution | Zenodo |
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| publishDate | 2024 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Machine learning for the assessment and mitigation of SMOG hazard in low-middle income developing countries Anjum, Sitara Rasheed, Rizwan Rashid Ahmed, Sajid Anjum, Sharoon Batool, Fizza Python Particulate Matter Air Pollution smog Health Risk Behaviors Pakistan <p><span>This is the first statistical research based on of five years of smog data from 2019 to 2023 in Lahore, using machine learning techniques. This research used machine learning techniques, namely using Python programming for data analysis. Python-based analyses can effectively assess regions with poor air quality and high pollution levels. This allows targeted interventions and restrictions to safeguard community health and avert respiratory disorders. </span></p> |
| title | Machine learning for the assessment and mitigation of SMOG hazard in low-middle income developing countries |
| topic | Python Particulate Matter Air Pollution smog Health Risk Behaviors Pakistan |
| url | https://doi.org/10.5281/zenodo.14236194 |