Abstract
Complexation-microfiltration process for removal of heavy metal ions such as lead, cadmium and zinc from water had been investigated. Two soluble derivates of cellulose was selected as complexing agents. The dependence of the removal efficiency from the operating parameters (pH value, pressure, concentration of metal ion, concentration of complexing agent and type of counter ion) was established. Two approaches of preparation of input data and two different artificial neural network architectures, general regression neural network and back-propagation neural network have been used for modeling of experimental data. The extrapolation ability of selected architectures, i.e., the prediction of rejection coefficient with inputs beyond the calibration range of original model, was also determined. The predictions were successful, and after evaluation of performances, the models that were developed gave relatively good results of mean absolute percentage error from 4 to 14% and R-squared from 0.717 to 0.852 for general regression neural network and from 0.897 to 0.955 for back-propagation neural network.
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Abbreviations
- P :
-
Operating pressure
- pH:
-
pH value
- C HM :
-
Concentration of heavy metal
- C CA :
-
Concentration of complexing agent
- R :
-
Rejection coefficient
- C p :
-
Concentration of heavy metal ion in permeate
- C f :
-
Concentration of heavy metal in feed solution
- n tr :
-
Number of training cases
- n wb :
-
Number of weights and biases
- N h :
-
Number of hidden neurons
- D j :
-
Euclidian distance
- W ij :
-
Weights
- f(D j):
-
Exponential function
- S 1 :
-
Summation unit for calculating sums of weighted outputs
- S 2 :
-
Summation unit for calculating sums of unweighted outputs
- ISF:
-
Individual smoothing factor
- RCA:
-
Relative contribution factor
- MAPE:
-
Mean absolute percentage error
- RMSE:
-
Root mean-squared error
- PBIAS:
-
Percent bias PBIAS
- O i :
-
Observed value
- P i :
-
Predicted value
- 1st IEHM :
-
First ionization energy
- r cov,HM :
-
Covalent diameter
- M HM :
-
Molar mass of used heavy metal solution
- M CA :
-
Molar mass of used complexing agent
- CpHM :
-
Concentration of heavy metal ion in permeate
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Acknowledgement
The authors acknowledge financial support from the Ministry of Education, Science and Technological Development of the Republic of Serbia, Project No. OI172007.
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Sekulić, Z., Antanasijević, D., Stevanović, S. et al. Application of artificial neural networks for estimating Cd, Zn, Pb removal efficiency from wastewater using complexation-microfiltration process. Int. J. Environ. Sci. Technol. 14, 1383–1396 (2017). https://doi.org/10.1007/s13762-017-1248-8
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DOI: https://doi.org/10.1007/s13762-017-1248-8