2015
DOI: 10.1063/1.4937255
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Prediction of the NO2 concentration data in an urban area using multiple regression and neuronal networks

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Cited by 11 publications
(7 citation statements)
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“…This study focuses on the dependence between meteorological factors including temperature, pressure, wind speed, wind direction, solar radiation, rainfall, and relative humidity and their influence on measured NO 2 concentration. The results indicated that MLP has a higher correlation coefficient than MLR in the forecasting of air quality and meteorological factors have an impact upon the NO 2 concentration 38 . Rahimi used MLP and MLR for prediction of the NO 2 and NO x concentrations according to meteorological variables.…”
Section: Discussionmentioning
confidence: 96%
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“…This study focuses on the dependence between meteorological factors including temperature, pressure, wind speed, wind direction, solar radiation, rainfall, and relative humidity and their influence on measured NO 2 concentration. The results indicated that MLP has a higher correlation coefficient than MLR in the forecasting of air quality and meteorological factors have an impact upon the NO 2 concentration 38 . Rahimi used MLP and MLR for prediction of the NO 2 and NO x concentrations according to meteorological variables.…”
Section: Discussionmentioning
confidence: 96%
“…Artificial Neural Network (ANN) models could be used as interpolation methods for complex and non-linear problems such as predicting and modeling air pollution 17,35,36 . Several research exhibits the performance of ANNs and traditional regression models to predict air pollutant concentrations 19,[37][38][39] . Dragomir et al compared the multiple linear regression and multilayer perceptron for the forecast of the NO 2 concentration in Romania.…”
Section: Discussionmentioning
confidence: 99%
“…So, the concentrations of PM 10 , NO 2 and SO 2 , in the studied area, were decreased, respectively, by 75%, 96% and 49% within few days after implementation of Covid-19 countermeasures. Several studies (Ocak and Turalioglu, 2008;Dragomir et al, 2015) argued the effect of meteorology on the atmospheric concentrations of traffic-related pollutants. While the role of the meteorological parameters is quite evident in this study, they are not quantified.…”
Section: Discussionmentioning
confidence: 99%
“…Additional parameters such as daily air temperature, solar radiation and air pressure might need to be included in the model to be able to estimate PM 2.5 concentration above 20 µg/m 3 . In 2015, a study was conducted to estimate the NO 2 concentration in Romania from 2009 to 2013 (5 years) by multiple linear regression (MLR) and artificial neural networks (ANNs), focusing on the dependence between meteorological parameters (such as air temperature, air pressure, wind speed, wind direction, solar radiation, rainfall and relative humidity) and their influence on measured NO 2 concentration [20]. Their results show that meteorological parameters have an impact on the NO 2 concentration although their estimation models have relatively low accuracy, which could have resulted from the measurement errors of the meteorological parameters.…”
Section: Introductionmentioning
confidence: 99%