… , a model using Artificial Neural Networks (ANN) has been developed to forecast pollutant
concentration of PM 10 , PM 2.5 , NO 2 , and O … with increased concentrations or not. Instead of …

… concentrations of RSP, NO x , and NO 2 in Mong Kok city, … 1, 2, and 3 days on prediction of
the current day concentrations of … PCA in improving the efficiency of neural network models in …

… Rourkela Steel Plant (RSP), is the first steel plant in public sector … SP but the model’s accuracy
was not improved and hence … for predicting RSPM and SPM concentrations over the study …

… using ensemble learning and linear regression based approaches, whereas, forecasting tasks
tend to implement neural networks … not just improved the spatial resolution of ground level …

… field of air pollution forecasting using artificial neural networks (ANNs) has increased
dramatically in recent years. However, the development of ANN models entails levels of uncertainty …

… a better understanding of the underlying mechanism of air … RSP are stronger than those
for O 3 , NO 2 , NO X and SO 2 . … Theoretically, shortcut connections in deep neural networks …

… of neural networks and fuzzy logic models (neuro-fuzzy model) … and better generalization
performance. For instance, the … modeling air pollutant parameters (CO, NO x , NO 2 , and RSP) …

… effort to enhance road traffic prediction through air quality … that measure traffic intensity and
air pollution levels. In several regions… an artificial neural network-based model which uses an …

… features required for prediction to improve the prediction time. The … models which are multi-layer
perceptron neural networks (… used to predict CO, NO2, NO, NOx, SO2, O3, and RSP. The …

… With Forecasting Models [34]: aims to monitor urban air pollution … Three improved neural
network models for air quality … of air quality data (CO, NO, NO 2 , SO 2 , NO x , O 3 , RSP), and …