Autoregressive models in environmental forecasting time series: a theoretical and application review
Though globalization, industrialization, and urbanization have escalated the economic
growth of nations, these activities have played foul on the environment. Better understanding …
growth of nations, these activities have played foul on the environment. Better understanding …
Multi-hour and multi-site air quality index forecasting in Beijing using CNN, LSTM, CNN-LSTM, and spatiotemporal clustering
R Yan, J Liao, J Yang, W Sun, M Nong, F Li - Expert Systems with …, 2021 - Elsevier
Effective air quality forecasting models are helpful for timely prevention and control of air
pollution. However, the spatiotemporal distribution characteristics of air quality have not …
pollution. However, the spatiotemporal distribution characteristics of air quality have not …
Air-pollution prediction in smart city, deep learning approach
Over the past few decades, due to human activities, industrialization, and urbanization, air
pollution has become a life-threatening factor in many countries around the world. Among …
pollution has become a life-threatening factor in many countries around the world. Among …
High granular and short term time series forecasting of air pollutant - a comparative review
Forecasting time series has acquired immense research importance and has vast
applications in the area of air pollution monitoring. This work attempts to investigate the …
applications in the area of air pollution monitoring. This work attempts to investigate the …
Nitrogen Dioxide (NO2) Pollution Monitoring with Sentinel-5P Satellite Imagery over Europe during the Coronavirus Pandemic Outbreak
Nitrogen dioxide (NO2) is one of the main air quality pollutants of concern in many urban
and industrial areas worldwide, and particularly in the European region, where in 2017 …
and industrial areas worldwide, and particularly in the European region, where in 2017 …
An integrated 3D CNN-GRU deep learning method for short-term prediction of PM2. 5 concentration in urban environment
This study proposes a new model for the spatiotemporal prediction of PM 2.5 concentration
at hourly and daily time intervals. It has been constructed on a combination of three …
at hourly and daily time intervals. It has been constructed on a combination of three …
Air quality prediction at new stations using spatially transferred bi-directional long short-term memory network
In the last decades, air pollution has been a critical environmental issue, especially in
developing countries like China. The governments and scholars have spent lots of effort on …
developing countries like China. The governments and scholars have spent lots of effort on …
An ARIMA-based study of bibliometric index prediction
Y Song, J Cao - Aslib Journal of Information Management, 2022 - emerald.com
Purpose The purpose of this paper is to predict bibliometric indicators based on ARIMA
models and to study the short-term trends of bibliometric indicators. Design/methodology …
models and to study the short-term trends of bibliometric indicators. Design/methodology …
A hybrid deep learning model for regional O3 and NO2 concentrations prediction based on spatiotemporal dependencies in air quality monitoring network
Short-term prediction of urban air quality is critical to pollution management and public
health. However, existing studies have failed to make full use of the spatiotemporal …
health. However, existing studies have failed to make full use of the spatiotemporal …
Integrated multiple directed attention-based deep learning for improved air pollution forecasting
In recent years, human health across the world is becoming concerned by a constant threat
of air pollution, which causes many chronic diseases and premature mortalities. Poor air …
of air pollution, which causes many chronic diseases and premature mortalities. Poor air …