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APPLICATION OF A NEURO-GENETIC TECHNIQUE IN THE OPTIMIZATION OF HEAVY METALS REMOVAL FROM WASTEWATERS FOR ENVIRONMENTAL RISK REDUCTION
Autori: Gabriel Dan Suditu
Data aparitiei: January 2013
Revista: Environmental Engineering and Management JournalVol. 12Nr. 1
ISSN: 1843 - 3707
Pret: 25.00 RON    
N.A.
Abstract
The reason for carrying out this research is related to the significant risk of heavy metals present in wastewater on the
environment and human health. The removal of heavy metal ions from aqueous solutions was performed in a batch system, using
peat (from Poiana Stampei, Romania) as adsorbent. The efficiency of the process was predicted with high accuracy (correlation
with experimental data more than 0.99) based on a feed-forward neural network with two hidden layers. The neural network
combined with a classical genetic algorithms have constituted the methodology applied for obtaining optimal working conditions
(temperature, contact time, initial concentration of heavy metal ions, solution pH, and adsorbent dose) which lead to maximum
efficiency. Important information for experimental practice are obtained, proven through the validation phase of the optimization
procedure.



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