Prediction method of PM2. 5 concentration based on decomposition and integration

H Yang, W Wang, G Li - Measurement, 2023 - Elsevier
With the acceleration of urbanization leading to a general decrease in air quality, accurate
PM2. 5 concentration prediction is of the utmost practical meaning for the control and …

Supervised Machine Learning Approaches for Predicting Key Pollutants and for the Sustainable Enhancement of Urban Air Quality: A Systematic Review

I Essamlali, H Nhaila, M El Khaili - Sustainability, 2024 - mdpi.com
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 …

Machine learning algorithm for delay prediction in iot and tactile internet

AR Abdellah, OA Mahmood, R Kirichek, A Paramonov… - Future Internet, 2021 - mdpi.com
The next-generation cellular systems, including fifth-generation cellular systems (5G), are
empowered with the recent advances in artificial intelligence (AI) and other recent …

Applying and comparing LSTM and ARIMA to predict CO levels for a time-series measurements in a port area

ED Spyrou, I Tsoulos, C Stylios - Signals, 2022 - mdpi.com
Air pollution is a major problem in the everyday life of citizens, especially air pollution in the
transport domain. Ships play a significant role in coastal air pollution, in conjunction with …

Particulate matter forecasting using different deep neural network topologies and wavelets for feature augmentation

SLJ Galvão, JCO Matos, YKL Kitagawa, FS Conterato… - Atmosphere, 2022 - mdpi.com
The concern about air pollution in urban areas has substantially increased worldwide. One
of its main components, particulate matter (PM) with aerodynamic diameter of≤ 2.5 µm …

Deep learning algorithms for prediction of PM10 dynamics in urban and rural areas of Korea

HS Choi, K Song, M Kang, Y Kim, KK Lee… - Earth Science …, 2022 - Springer
High concentrations of particulate matter (PM) are frequently associated with serious health
problems, underlining the importance of accurate PM prediction. This study aimed to predict …

A Hybrid Autoformer Network for Air Pollution Forecasting Based on External Factor Optimization

K Pan, J Lu, J Li, Z Xu - Atmosphere, 2023 - mdpi.com
Exposure to air pollution will pose a serious threat to human health. Accurate air pollution
forecasting can help people to reduce exposure risks and promote environmental pollution …

End-to-end Privacy Preserving Training and Inference for Air Pollution Forecasting with Data from Rival Fleets

G Gupta, K Ramesh, A Bhattacharya, D Gupta… - Cryptology ePrint …, 2023 - eprint.iacr.org
Privacy-preserving machine learning (PPML) promises to train machine learning (ML)
models by combining data spread across multiple data silos. Theoretically, secure multiparty …

[HTML][HTML] Enhanced Sequence-to-Sequence Attention-Based PM2.5 Concentration Forecasting Using Spatiotemporal Data

B Kim, E Kim, S Jung, M Kim, J Kim, S Kim - Atmosphere, 2024 - mdpi.com
Severe air pollution problems continue to increase because of accelerated industrialization
and urbanization. Specifically, fine particulate matter (PM 2.5) causes respiratory and …

An experimental comparison of classic statistical techniques on univariate time series forecasting

DR Khan, AB Patankar, A Khan - Procedia Computer Science, 2024 - Elsevier
In today's world, there is a high demand for understanding and analyzing patterns in time
series data in order to make accurate forecasts and predictions. Multiple univariate time …