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Corrigendum to "Assessing the effectiveness of artificial neural networks (ANN) and multiple linear regressions (MLR) in forecasting AQI and PM10 and evaluating health impacts through AirQ+ (case study: Tehran)" [Environ. Pollut., 338 (2023) 122623].
Shams SR, Kalantary S, Jahani A, Parsa Shams SM, Kalantari B, Singh D, Moeinnadini M, Choi Y. Shams SR, et al. Among authors: jahani a. Environ Pollut. 2024 Feb 1;342:123102. doi: 10.1016/j.envpol.2023.123102. Epub 2023 Dec 12. Environ Pollut. 2024. PMID: 38086164 No abstract available.
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 SR, Kalantary S, Jahani A, Parsa Shams SM, Kalantari B, Singh D, Moeinnadini M, Choi Y. Shams SR, et al. Among authors: jahani a. Environ Pollut. 2023 Dec 1;338:122623. doi: 10.1016/j.envpol.2023.122623. Epub 2023 Oct 6. Environ Pollut. 2023. PMID: 37806430
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