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Assessing the effectiveness of artificial neural networks (ANN) and multiple linear regressions (MLR) in forcasting AQI and PM10 and evaluating health impacts through AirQ+ (case study: Tehran).
Shams, Seyedeh Reyhaneh; Kalantary, Saba; Jahani, Ali; Parsa Shams, Seyed Mohammad; Kalantari, Behrang; Singh, Deveshwar; Moeinnadini, Mazaher; Choi, Yunsoo.
Affiliation
  • Shams SR; Department of Earth and Atmospheric Sciences, University of Houston, TX, 77204, USA.
  • Kalantary S; Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, 1416634793, Iran.
  • Jahani A; Research Center of Environment and Sustainable Development (RCESD): Tehran, Tehran, 141551156, Iran.
  • Parsa Shams SM; Department of Mechanical Engineering, College of Technical and Engineerin, Central Tehran University, Tehran, 1148963537, Iran.
  • Kalantari B; Department of Geography and Urban Planning, Shahid Beheshti University, Tehran, 1983969411, Iran.
  • Singh D; Department of Earth and Atmospheric Sciences, University of Houston, TX, 77204, USA.
  • Moeinnadini M; Department of Environment, Faculty of Natural Resources, Tehran University, Karaj, 1417935840, Iran.
  • Choi Y; Department of Earth and Atmospheric Sciences, University of Houston, TX, 77204, USA. Electronic address: ychoi23@central.uh.edu.
Environ Pollut ; 338: 122623, 2023 Dec 01.
Article de En | MEDLINE | ID: mdl-37806430
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Polluants atmosphériques / Pollution de l'air Type d'étude: Prognostic_studies / Risk_factors_studies Limites: Adult / Child / Humans Pays/Région comme sujet: Asia Langue: En Journal: Environ Pollut Sujet du journal: SAUDE AMBIENTAL Année: 2023 Type de document: Article Pays d'affiliation: États-Unis d'Amérique Pays de publication: Royaume-Uni
Texte intégral
Ajouter à My VHL
Imprimer
XML
PubMed Links
Recherche sur Google

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Polluants atmosphériques / Pollution de l'air Type d'étude: Prognostic_studies / Risk_factors_studies Limites: Adult / Child / Humans Pays/Région comme sujet: Asia Langue: En Journal: Environ Pollut Sujet du journal: SAUDE AMBIENTAL Année: 2023 Type de document: Article Pays d'affiliation: États-Unis d'Amérique Pays de publication: Royaume-Uni