Spatial estimation of urban air pollution with the use of artificial neural network models
A Alimissis, K Philippopoulos, CG Tzanis… - Atmospheric …, 2018 - Elsevier
The deterioration of urban air quality is considered worldwide one of the primary
environmental issues and scientific evidence associates the exposure to ambient air …
environmental issues and scientific evidence associates the exposure to ambient air …
Development and application of an automated air quality forecasting system based on machine learning
As one of the most concerned issues in modern society, air quality has received extensive
attentions from the public and the government, which promotes the continuous development …
attentions from the public and the government, which promotes the continuous development …
Environmental pollution and geo-ecological risk assessment of the Qhorveh mining area in western Iran
S Saedpanah, J Amanollahi - Environmental Pollution, 2019 - Elsevier
In order to evaluate the effect of mining activity on the environment of the Qhorveh mining
area in the west of Iran, the geological, ecological and environmental data, related to social …
area in the west of Iran, the geological, ecological and environmental data, related to social …
[PDF][PDF] Determination of optically inactive water quality variables using Landsat 8 data: A case study in Geshlagh reservoir affected by agricultural land use
T Vakili, J Amanollahi - J. Clean. Prod, 2020 - academia.edu
Water chemical variables such as total nitrogen (TN) and total phosphorus (TP) are soluble
and are optically inactive. Remote sensing (RS) technique is able to monitor the optical …
and are optically inactive. Remote sensing (RS) technique is able to monitor the optical …
Air quality data series estimation based on machine learning approaches for urban environments
A Rahimpour, J Amanollahi, CG Tzanis - Air Quality, Atmosphere & Health, 2021 - Springer
Air pollution is one of the main environmental problems in residential areas. In many cases,
the effects of air pollution on human health can be prevented by forecasting the air quality in …
the effects of air pollution on human health can be prevented by forecasting the air quality in …
Estimating half-hourly solar radiation over the Continental United States using GOES-16 data with iterative random forest
J Chen, W Zhu, Q Yu - Renewable Energy, 2021 - Elsevier
To reduce carbon emissions, using more solar energy is a feasible solution. Many
meteorological-based models can estimate global downward solar radiation (DSR), but they …
meteorological-based models can estimate global downward solar radiation (DSR), but they …
Developing ensemble mean models of satellite remote sensing, climate reanalysis, and land surface models
M Valipour, J Dietrich - Theoretical and Applied Climatology, 2022 - Springer
This study aims to access the selected satellite remote sensing, climate reanalysis, and land
surface models to estimate monthly land surface air temperature (LSAT), solar radiation …
surface models to estimate monthly land surface air temperature (LSAT), solar radiation …
Applying linear and nonlinear models for the estimation of particulate matter variability
CG Tzanis, A Alimissis, K Philippopoulos… - Environmental …, 2019 - Elsevier
In this study, data collected from an urban air quality monitoring network are being used for
the purpose of evaluating various methodologies used for spatial interpolation in the context …
the purpose of evaluating various methodologies used for spatial interpolation in the context …
Analysis of air pollution in the atmosphere due to firecrackers in the Diwali period over an urban Indian region
Short-term investigations of atmospheric pollutants (PM 10, PM 2.5, SO 2, NO 2, O 3, and
CO) were performed during the Diwali festival over Varanasi for a period of six years from …
CO) were performed during the Diwali festival over Varanasi for a period of six years from …
Spatial assessment of solar radiation by machine learning and deep neural network models using data provided by the COMS MI geostationary satellite: A case study …
Although data-driven methods including deep neural network (DNN) were introduced, there
was not enough assessment about spatial characteristics when using limited ground …
was not enough assessment about spatial characteristics when using limited ground …