Multi-source variational mode transfer learning for enhanced PM2. 5 concentration forecasting at data-limited monitoring stations
B Yao, G Ling, F Liu, MF Ge - Expert Systems with Applications, 2024 - Elsevier
Hybrid methods combining data decomposition with deep learning have recently exhibited
remarkable performance in PM2. 5 concentration forecasting. However, these methods still …
remarkable performance in PM2. 5 concentration forecasting. However, these methods still …
Interpreting hourly mass concentrations of PM2. 5 chemical components with an optimal deep-learning model
H Li, T Yang, Y Du, Y Tan, Z Wang - Journal of Environmental Sciences, 2025 - Elsevier
PM 2.5 constitutes a complex and diverse mixture that significantly impacts the environment,
human health, and climate change. However, existing observation and numerical simulation …
human health, and climate change. However, existing observation and numerical simulation …
PM2.5 Concentration Prediction Based on LightGBM Optimized by Adaptive Multi-Strategy Enhanced Sparrow Search Algorithm
X Liu, K Zhao, Z Liu, L Wang - Atmosphere, 2023 - mdpi.com
The atmospheric environment is of great importance to human health. However, its
influencing factors are complex and variable. An efficient technique is required to more …
influencing factors are complex and variable. An efficient technique is required to more …
Air Quality Index Prediction in Six Major Chinese Urban Agglomerations: A Comparative Study of Single Machine Learning Model, Ensemble Model, and Hybrid …
B Zhang, M Duan, Y Sun, Y Lyu, Y Hou, T Tan - Atmosphere, 2023 - mdpi.com
Air pollution is a hotspot of wide concern in Chinese cities. With the worsening of air
pollution, urban agglomerations face an increasingly complex environment for air quality …
pollution, urban agglomerations face an increasingly complex environment for air quality …
Pm2. 5 time series imputation with deep learning and interpolation
A Flores, H Tito-Chura, D Centty-Villafuerte… - Computers, 2023 - mdpi.com
Commonly, regression for time series imputation has been implemented directly through
regression models, statistical, machine learning, and deep learning techniques. In this work …
regression models, statistical, machine learning, and deep learning techniques. In this work …
An optimized back propagation neural network on small samples spectral data to predict nitrite in water
C Wang, G Zhang, J Yan - Environmental Research, 2024 - Elsevier
Accurate detection of pollutant levels in water bodies using fusion algorithms combined with
spectral data has become a critical issue for water conservation. However, the number of …
spectral data has become a critical issue for water conservation. However, the number of …