Supplemental Codes for "High Resolution Urban Air Quality Monitoring from Citizen Science Data with Ensemble Echo-State Transformer Networks" by Matthew Bonas and Stefano Castruccio
Simulated data "L96SimData.RData" with 40 variables (locations) and 1000 time points. This data is to be used in conjunction with the associated R and Python scripts to produce forecasts with the DESN and TNN models referenced in the manuscript.
R and Python scripts to produce forecasts on the simulated data for the DESN and TNN models. User should run the R script to produce forecasts for the DESN and to generate the data to to be used as input for the TNN.