Style | Citing Format |
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MLA | Shams SR, et al.. "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] (Environmental Pollution (2023) 338, (S0269749123016251), (10.1016/J.Envpol.2023.122623))." Environmental Pollution, vol. 342, no. , 2024, pp. -. |
APA | Shams SR, Kalantary S, Jahani A, Parsa Shams SM, Kalantari B, Singh D, Moeinnadini M, Choi Y (2024). 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] (Environmental Pollution (2023) 338, (S0269749123016251), (10.1016/J.Envpol.2023.122623)). Environmental Pollution, 342(), -. |
Chicago | Shams SR, Kalantary S, Jahani A, Parsa Shams SM, Kalantari B, Singh D, Moeinnadini M, Choi Y. "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] (Environmental Pollution (2023) 338, (S0269749123016251), (10.1016/J.Envpol.2023.122623))." Environmental Pollution 342, no. (2024): -. |
Harvard | Shams SR et al. (2024) '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] (Environmental Pollution (2023) 338, (S0269749123016251), (10.1016/J.Envpol.2023.122623))', Environmental Pollution, 342(), pp. -. |
Vancouver | Shams SR, Kalantary S, Jahani A, Parsa Shams SM, Kalantari B, Singh D, et al.. 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] (Environmental Pollution (2023) 338, (S0269749123016251), (10.1016/J.Envpol.2023.122623)). Environmental Pollution. 2024;342():-. |
BibTex | @article{ author = {Shams SR and Kalantary S and Jahani A and Parsa Shams SM and Kalantari B and Singh D and Moeinnadini M and Choi Y}, title = {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] (Environmental Pollution (2023) 338, (S0269749123016251), (10.1016/J.Envpol.2023.122623))}, journal = {Environmental Pollution}, volume = {342}, number = {}, pages = {-}, year = {2024} } |
RIS | TY - JOUR AU - Shams SR AU - Kalantary S AU - Jahani A AU - Parsa Shams SM AU - Kalantari B AU - Singh D AU - Moeinnadini M AU - Choi Y TI - 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] (Environmental Pollution (2023) 338, (S0269749123016251), (10.1016/J.Envpol.2023.122623)) JO - Environmental Pollution VL - 342 IS - SP - EP - PY - 2024 ER - |