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A critics study of neural networks applied to ion-exchange process

  • Authors: Kabuba, John , Mulaba-Bafubiandi, Antoine , Battle, Kim
  • Date: 2012
  • Subjects: Neural networks , Ion-exchange processes , Copper ions
  • Type: Article
  • Identifier: uj:6027 , ISBN 978-7-5647-1031-6 , http://hdl.handle.net/10210/10048
  • Description: This paper presents a critical study about the application of Neural Networks to ion-exchange process. Ion exchange is a complex non-linear process involving many factors influencing the ions uptake mechanisms from the pregnant solution. The following step includes the elution. Published data presents empirical isotherm equations with definite shortcomings resulting in unreliable predictions. Although Neural Network simulation technique encounters a number of disadvantages including its “black box”, and a limited ability to explicitly identify possible causal relationships, it has the advantage to implicitly handle complex nonlinear relationships between dependent and independent variables. In the present paper, the Neural Network model based on the back-propagation algorithm Levenberg-Marquardt was developed using a three layer approach with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and linear transfer function (purelin) at out layer. The above mentioned approach has been used to test the effectiveness in simulating ion exchange processes. The modeling results showed that there is an excellent agreement between the experimental data and the predicted values of copper ions removed from aqueous solutions.
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Structural equation modelling the leaching of oxidised copper-cobalt ore in HCl aqueous solution

  • Authors: Kime, Méschac-Bill , Mulaba-Bafubiandi, Antoine
  • Subjects: Leaching optimisation , Oxidised copper-cobalt ore , Structural Equation Modelling (SEM) , Multiple regression , Path analysis , Factor analysis , SPSS statistics
  • Language: English
  • Identifier: http://hdl.handle.net/10210/18571 , uj:16015 , Citation: Kime, M-B., Maluba-Bafubiandi, A. Structural equation modelling the leaching of oxidised copper-cobalt ore in HCl aqueous solution.
  • Description: Abstract: Structural Equation Modelling (SEM) is now widely used to explore the joint performance of factors affecting a process and to quantify the effect of each factor in the presence of the others. In this research work, SEM analysis was conducted to develop Structural Equation Models that well predict the leaching behaviour of Cu, Co, Ni and Fe in HCl aqueous solution of an oxidised copper-cobalt ore. A comprehensive set of experimental batch leaching tests was executed to study the effect of operating variables (pH, time, temperature and stirring speed) on the relative leaching yields of Cu, Co, Ni and Fe during the leaching of an oxidised copper-cobalt ore sample in an HCl aqueous solution. The gangue acid consumption was also measured to aid in understanding the behaviour of the gangue. The experimental results obtained were statistically analysed and modelled using the SEM procedure. The Structural Equation Models obtained showed that Cu and Co leaching yields had a strong positive dependence on both the leaching time and leaching temperature, while Fe leaching yield had a moderate dependence on the leaching temperature, stirring speed and the covariate Z (Z = stirring_speed*pH). On the contrary, Ni leaching yield had a strong negative dependence on both the stirring speed and the covariate Z. The Structural Equation Models agreed fairly with the experimental results obtained upon leaching. This is a clear indication that the models can be used to predict the leaching yields given a set of leaching parameters.
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Modeling of Co-Cu elution from clinoptilolite using neural network

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