Collaborative Learning at the Edge for Air Pollution Prediction
Author:
Affiliation:
1. School of Engineering, University of Warwick, Coventry, U.K.
2. Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Funder
Indonesia Endowment Fund for Education (LPDP), Ministry of Finance, the Republic of Indonesia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/19/10367905/10352366.pdf?arnumber=10352366
Reference51 articles.
1. Comparative Analysis of Machine Learning Techniques for Predicting Air Quality in Smart Cities
2. Estimation of missing air pollutant data using a spatiotemporal convolutional autoencoder
3. Declines in mental health associated with air pollution and temperature variability in China
4. The sectoral and regional economic consequences of outdoor air pollution to 2060
5. A critical review of the epidemiological evidence of effects of air pollution on dementia, cognitive function and cognitive decline in adult population
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