Geography-based Neural Networks for the Simulation of Air Pollution

Author:

Ferrari Luca,Guariso Giorgio

Funder

Fondazione Cariplo

Publisher

Elsevier BV

Subject

General Medicine

Reference14 articles.

1. Surrogate models to compute optimal air quality planning policies at a regional scale;Carnevale;Environmental Modelling & Software,2012

2. GST-GCN: A Geographic-Semantic-Temporal Graph Convolutional Network for Context-aware Traffic Flow Prediction on Graph Sequences;Chen,2020

3. Artificial neural networks forecasting of PM2.5 pollution using air mass trajectory based geographic model and wavelet transformation;Feng;Atmospheric Environment,2015

4. Spatial Variability Aware Deep Neural Networks (SVANN): A General Approach;Gupta;ACM Transactions on Intelligent Systems and Technology (TIST),2021

5. Towards spatial variability aware deep neural networks (SVANN): A summary of results;Gupta;arXiv preprint,2020

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