Deep learning for air pollutant concentration prediction: A review
Air pollution has become one of the critical environmental problem in the 21st century and
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
has attracted worldwide attentions. To mitigate it, many researchers have investigated the …
An extensive investigation on leveraging machine learning techniques for high-precision predictive modeling of CO2 emission
Predictive analytics utilizing machine learning algorithms play a pivotal role in various
domains, including the profiling of carbon dioxide (CO2) emissions. This research paper …
domains, including the profiling of carbon dioxide (CO2) emissions. This research paper …
A hybrid model with applying machine learning algorithms and optimization model to forecast greenhouse gas emissions with energy market data
ME Javanmard, SF Ghaderi - Sustainable Cities and Society, 2022 - Elsevier
In recent decades, many countries have encountered air pollution and environmental
problems caused by greenhouse gas (GHG) emissions. One of the essential approaches to …
problems caused by greenhouse gas (GHG) emissions. One of the essential approaches to …
A new perspective on air quality index time series forecasting: A ternary interval decomposition ensemble learning paradigm
Z Wang, R Gao, P Wang, H Chen - Technological Forecasting and Social …, 2023 - Elsevier
Accurate forecasting of the air quality index (AQI) plays a crucial role in taking precautions
against upcoming air pollution risks. However, air quality may fluctuate greatly in a certain …
against upcoming air pollution risks. However, air quality may fluctuate greatly in a certain …
Fault detection and calibration for building energy system using Bayesian inference and sparse autoencoder: A case study in photovoltaic thermal heat pump system
P Wang, C Li, R Liang, S Yoon, S Mu, Y Liu - Energy and Buildings, 2023 - Elsevier
The rise of clean energy such as solar energy provides a new idea to optimize the energy
structure, and Photovoltaic thermal (PVT) heat pump system is one of the mainstream …
structure, and Photovoltaic thermal (PVT) heat pump system is one of the mainstream …
A city-based PM2. 5 forecasting framework using Spatially Attentive Cluster-based Graph Neural Network model
Urban environments globally are under threat due to recent climate changes caused by a
variety of factors such as growing industrialization, rapid migration, increasing traffic flow …
variety of factors such as growing industrialization, rapid migration, increasing traffic flow …
Temporal convolutional denoising autoencoder network for air pollution prediction with missing values
In recent years, people are paying more attention to improve air quality levels to mitigate its
negative impact on human health. So, effective air pollution control has become one of the …
negative impact on human health. So, effective air pollution control has become one of the …
[HTML][HTML] Multi-layer perceptron's neural network with optimization algorithm for greenhouse gas forecasting systems
Abstract China, India, and the United States consume the most energy and emit the most
CO2. According to datacommons. org, India's CO2 emission is 1.80 tnes per capita, which is …
CO2. According to datacommons. org, India's CO2 emission is 1.80 tnes per capita, which is …
A novel hybrid model for six main pollutant concentrations forecasting based on improved LSTM neural networks
S Xu, W Li, Y Zhu, A Xu - Scientific Reports, 2022 - nature.com
In recent years, air pollution has become a factor that cannot be ignored, affecting human
lives and health. The distribution of high-density populations and high-intensity development …
lives and health. The distribution of high-density populations and high-intensity development …
An improved air quality index machine learning-based forecasting with multivariate data imputation approach
Accurate, timely air quality index (AQI) forecasting helps industries in selecting the most
suitable air pollution control measures and the public in reducing harmful exposure to …
suitable air pollution control measures and the public in reducing harmful exposure to …