Training architecture of the proposed system.

https://doi.org/10.1371/journal.pone.0138507.g002
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posted on 2015-09-28, 03:21 authored by Paulo S. G. de Mattos Neto, George D. C. Cavalcanti, Francisco Madeiro, Tiago A. E. Ferreira

<p>Training architecture of the proposed system.</p>

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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

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