Predicting the quality of air with machine learning approaches: Current research priorities and future perspectives
The spiraling growth of the world's population and unregulated urbanization have resulted in
many environmental problems, including poor quality of air, which is associated with a wide …
many environmental problems, including poor quality of air, which is associated with a wide …
Insights from citizen science reveal priority areas for conserving biodiversity in Bangladesh
The tropics contain a vast majority of species, yet our understanding of tropical biodiversity is
limited. Here we combine species locality data from scientific databases and social media to …
limited. Here we combine species locality data from scientific databases and social media to …
Potential of ARIMA-ANN, ARIMA-SVM, DT and CatBoost for Atmospheric PM2.5 Forecasting in Bangladesh
Atmospheric particulate matter (PM) has major threats to global health, especially in urban
regions around the world. Dhaka, Narayanganj and Gazipur of Bangladesh are positioned …
regions around the world. Dhaka, Narayanganj and Gazipur of Bangladesh are positioned …
Supervised Machine Learning Approaches for Predicting Key Pollutants and for the Sustainable Enhancement of Urban Air Quality: A Systematic Review
Urban air pollution is a pressing global issue driven by factors such as swift urbanization,
population expansion, and heightened industrial activities. To address this challenge, the …
population expansion, and heightened industrial activities. To address this challenge, the …
An improved pollution forecasting model with meteorological impact using multiple imputation and fine-tuning approach
Air pollution forecasting is a significant step for air quality pollution management to mitigate
pollution's negative impact on the environment and people's health. The data-driven …
pollution's negative impact on the environment and people's health. The data-driven …
Data-driven predictive modeling of PM2.5 concentrations using machine learning and deep learning techniques: a case study of Delhi, India
The present study intends to use machine learning (ML) and deep learning (DL) models to
forecast PM2. 5 concentration at a location in Delhi. For this purpose, multi-layer feed …
forecast PM2. 5 concentration at a location in Delhi. For this purpose, multi-layer feed …
Machine learning methods to forecast the concentration of PM10 in Lublin, Poland
J Kujawska, M Kulisz, P Oleszczuk, W Cel - Energies, 2022 - mdpi.com
Air pollution has a major impact on human health, especially in cities, and elevated
concentrations of PMx are responsible for a large number of premature deaths each year …
concentrations of PMx are responsible for a large number of premature deaths each year …
Estimating ground-level PM2.5 using subset regression model and machine learning algorithms in Asian megacity, Dhaka, Bangladesh
ARMT Islam, M Al Awadh, J Mallick, SC Pal… - Air Quality, Atmosphere …, 2023 - Springer
Abstract Fine particulate matter (PM2. 5) has become a prominent pollutant due to rapid
economic development, urbanization, industrialization, and transport activities, which has …
economic development, urbanization, industrialization, and transport activities, which has …
A deep learning approach to model daily particular matter of Ankara: Key features and forecasting
Y Akbal, KD Ünlü - International Journal of Environmental Science and …, 2022 - Springer
In this study, three different goals are pursued. Firstly, it is aimed to model particulate matter
(PM) of Ankara, the capital of Turkey, by utilizing hybrid deep learning methodology. To do …
(PM) of Ankara, the capital of Turkey, by utilizing hybrid deep learning methodology. To do …
Threatened species could be more vulnerable to climate change in tropical countries
S Chowdhury - Science of the Total Environment, 2023 - Elsevier
Climate change is a major threat impacting insects globally, yet the impact on tropical
insects is largely unknown. Here, I assessed the climatic vulnerability of Bangladeshi …
insects is largely unknown. Here, I assessed the climatic vulnerability of Bangladeshi …