The use of data-driven techniques such as artificial neural network (ANN) models for
outdoor air pollution forecasting has been popular in the past two decades. However …

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 …

Polycyclic aromatic hydrocarbons (PAHs) refer to a group of several hundred compounds,
among which 16 are identified as priority pollutants, due to their adverse health effects …

PM2. 5 concentration is an important index to measure the degree of air pollution. It is
necessary to establish an accurate PM2. 5 concentration prediction system for urban air …

This study introduces a forecasting model to help design an effective blood supply chain
mechanism for tackling the COVID-19 pandemic. In doing so, first, the number of people …

Air pollution due to air contamination by gases, liquids, and solid particles in suspension, is
a great environmental and public health concern nowadays. An important type of air …

Highly accurate forecasting of particulate matter concentration (PMC) is essential and
effective for establishing a reliable air pollution early warning system and has both …

Purpose The study aims to develop a multilayer high-effective ensemble of ensembles
predictive model (stacking ensemble) using several hyperparameter optimized ensemble …

The overheating of electronic devices has become very common with the advancement of
technology, requiring the development of new alternatives for thermal control. Due to their …

This study aimed to evaluate the mass concentration of size-resolved (PM1, PM2. 5, PM4,
PM10, PM100) particulate matter (PM) in the Wieliczka Salt Mine located in southern …