An overview of forecast analysis with ARIMA models during the COVID-19 pandemic: Methodology and case study in Brazil

R Ospina, JAM Gondim, V Leiva, C Castro - Mathematics, 2023‏ - mdpi.com
This comprehensive overview focuses on the issues presented by the pandemic due to
COVID-19, understanding its spread and the wide-ranging effects of government-imposed …

[HTML][HTML] Adapting machine learning for environmental spatial data-a review

M Jemeļjanova, A Kmoch, E Uuemaa - Ecological Informatics, 2024‏ - Elsevier
Large-scale modeling of environmental variables is an increasingly complex but necessary
task. In this paper, we review the literature on using machine learning to cope with …

[HTML][HTML] Prediction modelling framework comparative analysis of dissolved oxygen concentration variations using support vector regression coupled with multiple …

X Nong, C Lai, L Chen, D Shao, C Zhang, J Liang - Ecological Indicators, 2023‏ - Elsevier
Dissolved oxygen (DO) is an essential indicator for assessing water quality and managing
aquatic environments, but it is still a challenging topic to accurately understand and predict …

Computational deep air quality prediction techniques: a systematic review

M Kaur, D Singh, MY Jabarulla, V Kumar… - Artificial Intelligence …, 2023‏ - Springer
The escalating population and rapid industrialization have led to a significant rise in
environmental pollution, particularly air pollution. This has detrimental effects on both the …

Hybridization of rough set–wrapper method with regularized combinational LSTM for seasonal air quality index prediction

T Manna, A Anitha - Neural Computing and Applications, 2024‏ - Springer
In order to survive, mankind needs air. The quality of life depends on the purity of the air we
breathe in. Hazardous pollutants are stirred up in our environment by various activities …

An intelligent interval forecasting system based on fuzzy time series and error distribution characteristics for air quality index

H Yang, Y Gao, F Zhao, J Wang - Environmental Research, 2024‏ - Elsevier
Due to the emergency environment pollution problems, it is imperative to understand the air
quality and take effective measures for environmental governance. As a representative …

[HTML][HTML] A novel deep learning framework with a COVID-19 adjustment for electricity demand forecasting

Z Cui, J Wu, W Lian, YG Wang - Energy Reports, 2023‏ - Elsevier
Electricity demand forecasting is crucial for practical power system management. However,
during the COVID-19 pandemic, the electricity demand system deviated from normal system …

[HTML][HTML] A hybrid autoformer framework for electricity demand forecasting

Z Wang, Z Chen, Y Yang, C Liu, X Li, J Wu - Energy Reports, 2023‏ - Elsevier
Electricity demand forecasting is of great significance to the electricity system and residents'
life, but it is difficult to forecast the electricity demand series because of the influence of …

A novel AQI forecasting method based on fusing temporal correlation forecasting with spatial correlation forecasting

M Su, H Liu, C Yu, Z Duan - Atmospheric Pollution Research, 2023‏ - Elsevier
Air is an essential natural resource, and the Air Quality Index (AQI) is an important indicator
visually reflecting air quality. Accurate AQI prediction is critical for controlling air pollution …

A novel framework for high resolution air quality index prediction with interpretable artificial intelligence and uncertainties estimation

J Wu, X Chen, R Li, A Wang, S Huang, Q Li, H Qi… - Journal of …, 2024‏ - Elsevier
Accurate air quality index (AQI) prediction is essential in environmental monitoring and
management. Given that previous studies neglect the importance of uncertainty estimation …