Comparative evaluation of backpropagation neural network and genetic algorithm-backpropagation neural network models for PM2.5 concentration prediction based on aerosol optical depth, meteorological factors, and air pollutants

Global synthesis of two decades of research on improving PM2.5 estimation models from remote sensing and data science perspectives

(2023) Kaixu Bai et al.   EARTH-SCIENCE REVIEWS

Ambient Air Pollutant Exposures and COVID-19 Severity and Mortality in a Cohort of COVID-19 Patients in Southern California

(2022) Zhanghua Chen et al.   AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE

An Estimation Method for PM2.5 Based on Aerosol Optical Depth Obtained from Remote Sensing Image Processing and Meteorological Factors

(2022) Jilin Gu et al.   Remote Sensing

Remote sensing estimation of surface PM2.5 concentrations using a deep learning model improved by data augmentation and a particle size constraint

(2022) Shunchao Yin et al.   ATMOSPHERIC ENVIRONMENT

Ground PM2.5 prediction using imputed MAIAC AOD with uncertainty quantification

(2021) Qiang Pu et al.   ENVIRONMENTAL POLLUTION

Validation and comparison of high-resolution MAIAC aerosol products over Central Asia

(2021) Xiangyue Chen et al.   ATMOSPHERIC ENVIRONMENT

Synergistic data fusion of multimodal AOD and air quality data for near real-time full coverage air pollution assessment

(2021) Ke Li et al.   JOURNAL OF ENVIRONMENTAL MANAGEMENT

Construction of a virtual PM2.5 observation network in China based on high-density surface meteorological observations using the Extreme Gradient Boosting model

(2020) Ke Gui et al.   ENVIRONMENT INTERNATIONAL

Geographically and temporally weighted neural networks for satellite-based mapping of ground-level PM2.5

(2020) Tongwen Li et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

A Bayesian ensemble approach to combine PM2.5 estimates from statistical models using satellite imagery and numerical model simulation

(2019) Nancy L. Murray et al.   ENVIRONMENTAL RESEARCH

Deep Learning Architecture for Estimating Hourly Ground-Level PM2.5 Using Satellite Remote Sensing

(2019) Yibo Sun et al.   IEEE Geoscience and Remote Sensing Letters

Estimating 1-km-resolution PM2.5 concentrations across China using the space-time random forest approach

(2019) Jing Wei et al.   REMOTE SENSING OF ENVIRONMENT

Satellite-derived spatiotemporal PM2.5 concentrations and variations from 2006 to 2017 in China

(2019) Wenhao Xue et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Estimation of PM2.5 Concentrations in China Using a Spatial Back Propagation Neural Network

(2019) Weilin Wang et al.   Scientific Reports

PM 2.5 forecasting using SVR with PSOGSA algorithm based on CEEMD, GRNN and GCA considering meteorological factors

(2018) Suling Zhu et al.   ATMOSPHERIC ENVIRONMENT

Impact of synoptic weather patterns on 24 h-average PM 2.5 concentrations in the North China Plain during 2013–2017

(2018) Hao Zhang et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Spatio-Temporal Pattern Estimation of PM2.5 in Beijing-Tianjin-Hebei Region Based on MODIS AOD and Meteorological Data Using the Back Propagation Neural Network

(2018) Xiliang Ni et al.   Atmosphere

LSTM network: a deep learning approach for short-term traffic forecast

(2017) Zheng Zhao et al.   IET Intelligent Transport Systems

Time series forecasting using a deep belief network with restricted Boltzmann machines

(2014) Takashi Kuremoto et al.   NEUROCOMPUTING