Extended deep learning for air pollution forecast enhancement: validation and demonstration

Project Member(s): Ha, Q.

Funding or Partner Organisation: NSW Department of Planning, Industry and Environment
NSW Department of Planning, Industry and Environment

Start year: 2022

Publications:

Le, TH, Nguyen, HAD, Barthelemy, X, Nguyen, TT, Ha, QP, Jiang, N, Duc, H, Azzi, M & Riley, M 1970, 'Visualization Platform for Multi-Scale Air Pollution Monitoring and Forecast', 2024 IEEE/SICE International Symposium on System Integration (SII), 2024 IEEE/SICE International Symposium on System Integration (SII), IEEE, pp. 01-06.
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Nguyen, HAD, Ha, QP, Duc, H, Azzi, M, Jiang, N, Barthelemy, X & Riley, M 2023, 'Long Short-Term Memory Bayesian Neural Network for Air Pollution Forecast', IEEE Access, vol. 11, pp. 35710-35725.
View/Download from: Publisher's site

FOR Codes: Air quality, Automation engineering

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.