Study of Montmorillonite Clay for the Removal of Copper (II) by Adsorption: Full Factorial Design Approach and Cascade Forward Neural Network
An intensive study has been made of the removal efficiency of Cu(II) from industrial leachate by biosorption of montmorillonite. A 24 factorial design and cascade forward neural network (CFNN) were used to display the significant levels of the analyzed factors on the removal efficiency. The obtained...
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Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
Wiley
2013-01-01
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Series: | The Scientific World Journal |
Online Access: | http://dx.doi.org/10.1155/2013/342628 |
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