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 …
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
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 …
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 …
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
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 …
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 …
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
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 …
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 …
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
Privacy-preserving machine learning (PPML) promises to train machine learning (ML)
models by combining data spread across multiple data silos. Theoretically, secure multiparty …
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 …
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 …
series data in order to make accurate forecasts and predictions. Multiple univariate time …