[HTML][HTML] Multi-Step Ahead Ex-Ante Forecasting of Air Pollutants Using Machine Learning
In this study, a novel general multi-step ahead strategy is developed for forecasting time
series of air pollutants. The values of the predictors at future moments are gathered from …
series of air pollutants. The values of the predictors at future moments are gathered from …
Air pollution forecasting for Tehran city using vector auto regression
F Gholamzadeh, S Bourbour - 2020 6th Iranian Conference on …, 2020 - ieeexplore.ieee.org
Recently, in many urban areas, air quality has decreased because of human activities such
as biomass burning and development of industrialization. There are some harmful pollutants …
as biomass burning and development of industrialization. There are some harmful pollutants …
A novel approach for prediction of air pollutant concentration
LR Deepthi, CG Amruta, D Krishnan… - … on Trends in …, 2020 - ieeexplore.ieee.org
Air pollution is one of the biggest concerns India is facing today. It has been increased due
to urbanisation and industrialisation. In this paper, the proposed model uses time series …
to urbanisation and industrialisation. In this paper, the proposed model uses time series …
[PDF][PDF] A review on short-term prediction of air pollutant concentrations
In the attempt to increase the production of the industrial sector to accommodate human
needs; motor vehicles and power plants have led to the decline of air quality. The …
needs; motor vehicles and power plants have led to the decline of air quality. The …
Air pollution forecasting using multiple time series approach
KN Tejasvini, GR Amith, Akhtharunnisa… - Proceedings of the Global …, 2020 - Springer
Air pollution forecasting helps to take precautionary measures in order to maintain public
health. Time series algorithms and software such as Prophet package are used to forecast …
health. Time series algorithms and software such as Prophet package are used to forecast …
Air quality forecasting using artificial neural networks with real time dynamic error correction in highly polluted regions
Air pollution is an important issue, especially in megacities across the world. There are
emission sources within and also in the regions around these cities, which cause …
emission sources within and also in the regions around these cities, which cause …
An online air pollution forecasting system using neural networks
In this work, an online air pollution forecasting system for Greater Istanbul Area is
developed. The system predicts three air pollution indicator (SO2, PM10 and CO) levels for …
developed. The system predicts three air pollution indicator (SO2, PM10 and CO) levels for …
Hourly pollutants forecasting using a deep learning approach to obtain the AQI
JA Moscoso-López, J González-Enrique… - Logic Journal of the …, 2023 - academic.oup.com
Abstract The Air Quality Index (AQI) shows the state of air pollution in a unique and more
understandable way. This work aims to forecast the AQI in Algeciras (Spain) 8 hours in …
understandable way. This work aims to forecast the AQI in Algeciras (Spain) 8 hours in …
[HTML][HTML] MultiStep ahead forecasting for hourly PM10 and PM2. 5 based on two-stage decomposition embedded sample entropy and group teacher optimization …
F Jiang, Y Qiao, X Jiang, T Tian - Atmosphere, 2021 - mdpi.com
The randomness, nonstationarity and irregularity of air pollutant data bring difficulties to
forecasting. To improve the forecast accuracy, we propose a novel hybrid approach based …
forecasting. To improve the forecast accuracy, we propose a novel hybrid approach based …
Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations
The new method for the forecasting hourly concentrations of air pollutants is presented in the
paper. The method was developed for a site in urban residential area in city of Zagreb …
paper. The method was developed for a site in urban residential area in city of Zagreb …