{
  "id": 9998,
  "url": "https://doi.org/10.1038/s41598-025-34278-8",
  "title": "Air quality index AQI classification based on hybrid particle swarm and grey wolf optimization with ensemble machine learning model",
  "summary": "Accurate Air Quality Index (AQI) classification is essential for environmental surveillance and public health decision-making. Using a publicly available daily U.S. county-level dataset with six AQI categories (Good, Moderate, Unhealthy for Sensitive Groups, Unhealthy, Very Unhealthy, Hazardous), we conducted a comprehensive benchmarking study. Data preprocessing included missing-value imputation and class balancing via Synthetic Minority Over-sampling Technique (SMOTE). We trained and evaluated",
  "authors": "Emad Elabd, Hany Mohamed Hamouda, M. A. Mohamed Ali, A. S. Hamid, Yasser Fouad",
  "category": "research",
  "topics": "privacy-surveillance,healthcare,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-01-05T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:34:04.102Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/9998",
  "original_url": "https://doi.org/10.1038/s41598-025-34278-8",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}