Enhancement of heavy metals sorption via nanocomposites of rice straw and Fe3O4 nanopeprintss using artificial neural network (ANN)

Enhancement of heavy metals sorption via nanocomposites of rice straw and Fe3O4 nanopeprintss using artificial neural network (ANN)

The artificial neural network (ANN) modeling of adsorption of Pb(II) and Cu(II) was carried out for determination of the optimum values of the variables to get the maximum removal efficiency. The input variables were initial ion concentration, adsorbent dosage, and removal time, while the removal ef...

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Bibliographic Details
Main Authors: Khandanlou, Roshanak, Fard Masoumi, Hamid Reza, Ahmad @ Ayob, Mansor, Shameli, Kamyar, Basri, Mahiran, Kalantari, Katayoon
Format: Article
Language:English
Published: Elsevier 2016
Subjects:
Artificial neural network (ANN); Adsorption; Removal efficiency; Heavy metal; Topologies
Online Access:http://psasir.upm.edu.my/id/eprint/54168/
http://psasir.upm.edu.my/id/eprint/54168/1/Enhancement%20of%20heavy%20metals%20sorption%20via%20nanocomposites%20of%20rice%20straw.pdf

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