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[HTML][HTML] Hazard susceptibility map** with machine and deep learning: a literature review
With the increase in climate-change-related hazardous events alongside population
concentration in urban centres, it is important to provide resilient cities with tools for …
concentration in urban centres, it is important to provide resilient cities with tools for …
Predicting next hour fine particulate matter (PM2. 5) in the Istanbul Metropolitan City using deep learning algorithms with time windowing strategy
Poor air quality has various detrimental physical and mental effects on human health and
quality of life. In particular, PM 2.5 air pollution has been associated with cardiovascular and …
quality of life. In particular, PM 2.5 air pollution has been associated with cardiovascular and …
[HTML][HTML] Effective air pollution prediction by combining time series decomposition with stacking and bagging ensembles of evolving spiking neural networks
In this article, we introduce a new approach to air pollution prediction using the CEEMDAN
time series decomposition method combined with the two-layered ensemble of predictors …
time series decomposition method combined with the two-layered ensemble of predictors …
A comparison of machine learning methods to forecast tropospheric ozone levels in Delhi
EK Juarez, MR Petersen - Atmosphere, 2021 - mdpi.com
Ground-level ozone is a pollutant that is harmful to urban populations, particularly in
develo** countries where it is present in significant quantities. It greatly increases the risk …
develo** countries where it is present in significant quantities. It greatly increases the risk …
Prediction of air pollutant concentration based on one-dimensional multi-scale CNN-LSTM considering spatial-temporal characteristics: A case study of **'an, China
H Dai, G Huang, J Wang, H Zeng, F Zhou - Atmosphere, 2021 - mdpi.com
Air pollution has become a serious problem threatening human health. Effective prediction
models can help reduce the adverse effects of air pollutants. Accurate predictions of air …
models can help reduce the adverse effects of air pollutants. Accurate predictions of air …
Attention-based distributed deep learning model for air quality forecasting
AG Mengara Mengara, E Park, J Jang, Y Yoo - Sustainability, 2022 - mdpi.com
Air quality forecasting has become an essential factor in facilitating sustainable development
worldwide. Several countries have implemented monitoring stations to collect air pollution …
worldwide. Several countries have implemented monitoring stations to collect air pollution …
Fuzzy inference system tree with particle swarm optimization and genetic algorithm: a novel approach for PM10 forecasting
World health organization's estimates reveal that air pollution kills almost 6.5 million people
in the world every year. As human beings, on average, spend 80–90% of their routine time …
in the world every year. As human beings, on average, spend 80–90% of their routine time …
[HTML][HTML] Current Situation and Prospect of Geospatial AI in Air Pollution Prediction
Faced with increasingly serious environmental problems, scientists have conducted
extensive research, among which the importance of air quality prediction is becoming …
extensive research, among which the importance of air quality prediction is becoming …
Forecasting PM2. 5 concentration using a single-dense layer BiLSTM method
In recent times, particulate matter (PM2. 5) is one of the most critical air quality contaminants,
and the rise of its concentration will intensify the hazard of cleanrooms. The forecasting of …
and the rise of its concentration will intensify the hazard of cleanrooms. The forecasting of …
A machine learning-based ensemble model for estimating diurnal variations of nitrogen oxide concentrations in Taiwan
Air pollution is inextricable from human activity patterns. This is especially true for nitrogen
oxide (NO x), a pollutant that exists naturally and also as a result of anthropogenic factors …
oxide (NO x), a pollutant that exists naturally and also as a result of anthropogenic factors …