A graph-based LSTM model for PM2.5 forecasting

Forecasting Severe Weather with Random Forests

(2020) Aaron J. Hill et al.   MONTHLY WEATHER REVIEW

An LSTM-based aggregated model for air pollution forecasting

(2020) Yue-Shan Chang et al.   Atmospheric Pollution Research

Spatiotemporal prediction of air quality based on LSTM neural network

(2020) Dewen Seng et al.   Alexandria Engineering Journal

A hybrid model for spatiotemporal forecasting of PM2.5 based on graph convolutional neural network and long short-term memory

(2019) Yanlin Qi et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Improving text classification with weighted word embeddings via a multi-channel TextCNN model

(2019) Bao Guo et al.   NEUROCOMPUTING

Development of a stacked ensemble model for forecasting and analyzing daily average PM 2.5 concentrations in Beijing, China

(2018) Binxu Zhai et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Multi-output support vector machine for regional multi-step-ahead PM2.5 forecasting

(2018) Yanlai Zhou et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Assessing the impact of fine particulate matter (PM 2.5 ) on respiratory-cardiovascular chronic diseases in the New York City Metropolitan area using Hierarchical Bayesian Model estimates

(2016) Stephanie A. Weber et al.   ENVIRONMENTAL RESEARCH

The forecasting research of early warning systems for atmospheric pollutants: A case in Yangtze River Delta region

(2015) Yiliao Song et al.   ATMOSPHERIC ENVIRONMENT

Future prediction of surface ozone over east Asia using Models-3 Community Multiscale Air Quality Modeling System and Regional Emission Inventory in Asia

(2008) Kazuyo Yamaji et al.   JOURNAL OF GEOPHYSICAL RESEARCH