Simulation and Optimization of Biosorption Studies for Prediction of Sorption Efficiency of Leucaena Leucocephala Seeds for the Removal of Ni (II) From Waste Water

  • J. K. Arora
  • S. Srivastava


Simulation and optimization of biosorption studies were carried out using Artificial Neural Network (ANN) modeling. A single layer ANN model was developed to simulate the process and to predict the removal efficiency of Ni (II) ions from aqueous solution using Leucaena Leucocephala seed powder (LLSP). Different NN architecture was tested by varying network topology. The findings indicated that the ANN provided reasonable predictive performance. The influence of each parameter on the variable studied was assessed, and metal concentration, contact time, biomass dosage and initial volume were found to be the most significant factors. Simulations based on the developed ANN model can estimate the behavior of the biosorption phenomenon process under different conditions.


Artificial Neural Network Mean Square Error Minimum Mean Square Error Back Propagation Algorithm Back Propagation Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • J. K. Arora
    • 1
  • S. Srivastava
    • 2
  1. 1.Department of MathematicsTechnical CollegeAgraIndia
  2. 2.Department of Chemistry, Faculty of ScienceDayalbagh Educational InstituteAgraIndia

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