scholarly journals A Survey On Air Quality Prediction Using Traditional Statistics Method

2020 ◽  
pp. 942-946
Author(s):  
S. Karthikeyani ◽  
S. Rathi
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Meteorological Parameters ◽  
Moving Average ◽  
Quality Prediction ◽  
Atmospheric Air ◽  
Air Quality Prediction ◽  
Naive Method ◽  
Auto Regressive ◽  
Weighted Moving Average

Air pollution is the release of pollutants into the atmospheric air which are harmful to human health and the planet as a whole. Car emissions, dust, pollen, chemicals from factories and mold spores may be suspended as a particle. In this survey, the analyzes are made revolving on air quality prediction using the traditional statistics method. The prediction using air pollutants are PM2.5, PM10, NO2, NOx, NO, SO2, CO, O3 and meteorological parameters such as Absolute Temparathure(AT) and Relative Humidity(RH). In this comparison experiments, common predicted algorithms are Naive Method, Auto-Regressive Integrated Moving Average(ARIMA), Exponentially Weighted Moving Average(EWMA), Linear Regression(LR), LSTM model, Prophet Model are analyzed.

scholarly journals Modeling of Nonlinear Autoregressive Neural Network for Multi-Step Ahead Air Quality Prediction

TEM Journal ◽  
2020 ◽  
pp. 852-861
Author(s):  
Mirza Pasic ◽  
Izet Bijelonja ◽  
Edin Kadric ◽  
Hadis Bajric
Keyword(s):  
Neural Network ◽  
Air Pollutants ◽  
Meteorological Parameters ◽  
Network Models ◽  
Quality Prediction ◽  
Optimal Model ◽  
Neural Network Models ◽  
Air Quality Prediction ◽  
Nonlinear Autoregressive ◽  
Autoregressive Neural Network

In this paper five neural network models were developed using NARX-SP neural network type in order to predict air pollutants concentrations (SO2, PM10, NO2, O3 and CO ) for the 72nd hour ahead for Sarajevo. Hourly values of air pollutants concentrations and meteorological parameters (air temperature, pressure and humidity, wind speed and direction) for Sarajevo were used. Optimal model was selected based on the values of R2, MSE and the complexity of models. Optimal neural network model can predict air pollutants concentrations for the 72nd hour ahead with high accuracy, as well as for all hours up to 72nd hour.

scholarly journals Research on air quality prediction method in Hangzhou based on machine learning

2021 ◽  
Vol 2010 (1) ◽  
pp. 012011
Author(s):  
Zhongjie Fu ◽  
Haiping Lin ◽  
Bingqiang Huang ◽  
Jiana Yao
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Prediction Method ◽  
Quality Prediction ◽  
Air Quality Prediction

The use of MODIS data and aerosol products for air quality prediction

2004 ◽  
Vol 38 (30) ◽  
pp. 5057-5070 ◽  
Author(s):  
Keith D. Hutchison ◽  
Solar Smith ◽  
Shazia Faruqui
Keyword(s):  
Air Quality ◽  
Quality Prediction ◽  
Modis Data ◽  
Air Quality Prediction
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