GRU for Overcoming Seasonality and Trend in PM2.5 Air Pollution Forecasting
Pollution forecasting is important to research, especially for hazardous particles like PM 2.5.
However, trends and seasonality that can hide in the dataset make the forecasting model's …
However, trends and seasonality that can hide in the dataset make the forecasting model's …
Air Pollution Forecasting Using Multimodal Data
MA Ton-Thien, CT Nguyen, QM Le, DQ Duong… - … Conference on Industrial …, 2023 - Springer
Air pollution is one of the most concerning problems worldwide. It leads to the necessary
time series forecasting of particulate matter (PM) concentrations. In this study, we propose …
time series forecasting of particulate matter (PM) concentrations. In this study, we propose …
Pm2. 5 spatial-temporal long series forecasting based on deep learning and emd
Q Zhang, G Yang, E Yuan - International Symposium on Knowledge and …, 2022 - Springer
With the accelerated urbanization and industrialization, air pollution has become an
important issue that affects the daily economy as well as development. By the formation of …
important issue that affects the daily economy as well as development. By the formation of …
Deep learning models for air pollution forecasting in Seoul South Korea
U Kiftiyani, SA Nazhifah - 2021 International Conference on …, 2021 - ieeexplore.ieee.org
Air pollution has been a major cause of health problems in several countries such as South
Korea which is a country with rapid industrial and population growth, it urges the …
Korea which is a country with rapid industrial and population growth, it urges the …
PM2. 5 Pollution Prediction Service based on Mogrifier LSTM Model
J Liu, M Lian - 2023 IEEE 29th International Conference on …, 2023 - ieeexplore.ieee.org
Accurate PM2. 5 concentration forecasting service is essential for reducing the impacts of
this air pollution. In this paper, we propose a novel PM2. 5 pollution prediction service to …
this air pollution. In this paper, we propose a novel PM2. 5 pollution prediction service to …
Computational Forecast of PM2. 5 Pollution Based on Gas Emission and Traffic Volume Observations
CH Fan, S Khuntia, SY Fan, PH Juan… - 2022 IEEE 5th …, 2022 - ieeexplore.ieee.org
Air pollution has recently been a prevalent issue due to the fast development of cities in
countries. Thus, issues related to particulate matter, PM2. 5 have been investigated as it is a …
countries. Thus, issues related to particulate matter, PM2. 5 have been investigated as it is a …
Multi-feature pm2. 5 prediction with arima-lstm
J Xiao, Q Wang, J Cui, J Yu - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
One of the most harmful environmental risk to human health is air pollution. Effective
prediction of pollutants in the air is conducive to air improvement and pollution control. Air …
prediction of pollutants in the air is conducive to air improvement and pollution control. Air …
PM2.5 Concentration Forecasting Using Weighted Bi-LSTM and Random Forest Feature Importance-Based Feature Selection
B Kim, E Kim, S Jung, M Kim, J Kim, S Kim - Atmosphere, 2023 - mdpi.com
Particulate matter (PM) in the air can cause various health problems and diseases in
humans. In particular, the smaller size of PM 2.5 enable them to penetrate deep into the …
humans. In particular, the smaller size of PM 2.5 enable them to penetrate deep into the …
A Comparative Study of Features Selection in the Context of Forecasting PM2. 5 Concentration
A Aboualnour, M Shalaby, E Elsamahy - World Conference on Internet of …, 2023 - Springer
Air pollution is a critical issue for our world today, the emissions of air pollutants cause
serious environmental and health issues. In this the main objective is to forecast one of the …
serious environmental and health issues. In this the main objective is to forecast one of the …
PM2. 5 forecasting model using a combination of deep learning and statistical feature selection
This paper proposed a PM 2.5 forecasting model using Long Short-Term Model (LSTM)
sequence to sequence combined with the statistical method. Correlation Analysis, XGBoost …
sequence to sequence combined with the statistical method. Correlation Analysis, XGBoost …