Modeling, optimization and understanding of adsorption process for pollutant removal via machine learning: Recent progress and future perspectives
W Zhang, W Huang, J Tan, D Huang, J Ma, B Wu - Chemosphere, 2023 - Elsevier
It is crucial to reduce the concentration of pollutants in water environment to below safe
levels. Some cost-effective pollutant removal technologies have been developed, among …
levels. Some cost-effective pollutant removal technologies have been developed, among …
Predict the effect of meteorological factors on haze using BP neural network
Rapid urbanization and economic growth in China have resulted in severe haze. PM2. 5 is a
key component of haze. Using machine learning to predict PM2. 5 concentrations has …
key component of haze. Using machine learning to predict PM2. 5 concentrations has …
Roles of Artificial Intelligence and Machine Learning in Enhancing Construction Processes and Sustainable Communities
Machine Learning (ML), a subset of Artificial Intelligence (AI), is gaining popularity in the
architectural, engineering, and construction (AEC) sector. This systematic study aims to …
architectural, engineering, and construction (AEC) sector. This systematic study aims to …
Air quality monitoring based on chemical and meteorological drivers: Application of a novel data filtering-based hybridized deep learning model
Particulate matter (PM) or particle pollution include the tiny particles of dust and fly ash
particles are expelled from coal-burning power plants. Coal combustion is an extremely …
particles are expelled from coal-burning power plants. Coal combustion is an extremely …
Machine learning-based white-box prediction and correlation analysis of air pollutants in proximity to industrial zones
The adverse health effects caused by long-term exposure to high pollution volumes from
industries near urban areas are a growing concern. Determining accurate distribution …
industries near urban areas are a growing concern. Determining accurate distribution …
Understanding the Disparities of PM2. 5 Air Pollution in Urban Areas via Deep Support Vector Regression
In densely populated urban areas, PM2. 5 has a direct impact on the health and quality of
residents' life. Thus, understanding the disparities of PM2. 5 is crucial for ensuring urban …
residents' life. Thus, understanding the disparities of PM2. 5 is crucial for ensuring urban …
Influence of urban spatial and socioeconomic parameters on PM2. 5 at subdistrict level: A land use regression study in Shenzhen, China
L Zeng, J Hang, X Wang, M Shao - Journal of Environmental Sciences, 2022 - Elsevier
The intraurban distribution of PM 2.5 concentration is influenced by various spatial,
socioeconomic, and meteorological parameters. This study investigated the influence of 37 …
socioeconomic, and meteorological parameters. This study investigated the influence of 37 …
Spatiotemporal prediction of particulate matter concentration based on traffic and meteorological data
Air pollution threatens worldwide human health, ecosystems, and climate change.
Transportation is a major contributor to air pollution. However, the link between …
Transportation is a major contributor to air pollution. However, the link between …
Interpretable CEEMDAN-FE-LSTM-transformer hybrid model for predicting total phosphorus concentrations in surface water
J Yao, S Chen, X Ruan - Journal of Hydrology, 2024 - Elsevier
The complexity of the biogeochemical cycle of phosphorus in lakes makes it challenging to
produce efficient and accurate predictions of total phosphorus (TP) concentrations. In this …
produce efficient and accurate predictions of total phosphorus (TP) concentrations. In this …
The influence of neighborhood-level urban morphology on PM2. 5 variation based on random forest regression
To improve the atmospheric environment by optimizing urban morphology, this study
develops a random forest (RF) model to investigate the influence of urban morphology on …
develops a random forest (RF) model to investigate the influence of urban morphology on …