10.1371/journal.pone.0138507.g002
Paulo S. G. de Mattos Neto
Paulo
S. G. de Mattos Neto
George D. C. Cavalcanti
George
D. C. Cavalcanti
Francisco Madeiro
Francisco
Madeiro
Tiago A. E. Ferreira
Tiago
A. E. Ferreira
Training architecture of the proposed system.
Public Library of Science
2015
ga
Artificial neural networks
approach
correction
PM 10 concentration series
High PM concentration
hs
residuals modeling
fitness function
ann
PM forecasters
forecasting method
performance
Experimental results show
PM time series
2015-09-28 03:21:04
Figure
https://plos.figshare.com/articles/figure/_Training_architecture_of_the_proposed_system_/1558898
<p>Training architecture of the proposed system.</p>