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Year 2020, Volume: 4 Issue: 1, 1 - 22, 27.03.2020

Abstract

References

  • [1]. Lalvani, S.B.; Wiltowski, T., and Weston, A., (2010), Metal ions removal from wastewater by adsorption, Journal of Engineering Science, Vol. 2, pp 877-879
  • [2]. Ong, S.; Seng, C., and Lim, P., (2007), Kinetics of adsorption of copper (II) and cadmium (II) from aqueous solution on rice husk and modified rice husk, Electronic Journal of Environmental Agriculture and food Chemistry, Vol. 6(2), pp 1764-1774.
  • [3]. Kumar, N.K; Reddy, D.S.R and Venkateswarlu, P (2010), Application of response surface methodology for optimization of chromium biosorption from aqueous solution onto Syzigium Cumini (Java) seed powder, Microbial and Biochemical Technology, vol. 2(1), pp; 020-027
  • [4]. Lima, E.C; Betina, R; Vaghetti, J.C.P; Brasil, J.L; Nathalia, M.S; Dos-Santos Jr., A.A; Pavan, F.A; Silvio, L.P.D; Edilson, V.B and Da-Silva, E.A (2007), Adsorption of Cu(II) on Araucaria Augustifolia wastes; determination of the optimal conditions by statistical design of experiment, Journal of Hazardous Materials, vol. 140(1), pp; 211-220
  • [5]. Lin, S. H., and Juang, R.S., (2002), Heavy metal removal from water by sorption using surfactant-modified montmorillonite, Journal of Hazardous Materials, vol. B92, pp 315 – 322
  • [6]. Weng, C.H; Tsai, C.Z; Chu, S.H and Sharma, Y.C., (2007), Adsorption characteristics of copper (II) onto spent activated clay, Separation Purification Technology Journal, vol. 54, pp; 187-197
  • [7]. Sinan, M.T; Beytullah, E and Asude, A (2011), Prediction of adsorption efficiency for the removal of Ni(II) ions by zeolite using artificial neural network (ANN) approach, Fresenius Environmental Bulletin, vol. 20(12), pp; 3158-3165
  • [8]. Mohammed, Y; Farahnaz, E.B; Sepideh, K.B; Bahador, D.J; Soraya, H; Mohammad, R.M and Lugman, A.C (2013), Removal of Ni(II) from aqueous solution by an electric arc furnace slag using artificial neural network (ANN) approach, Advance in Environmental Biology, vol. 7(9), pp; 2303-2310
  • [9]. Abdoliman, A; Ali, A.A and Fatemeh, A (2013), A study of cadmium removal from aqueous solution by sunflower powder and its modeling using artificial neural network (ANN), Iranian Journal of Health Sciences, vol. 1(3), pp; 28-34
  • [10]. Abhishek, K; Kumar, R.R; Jyoti, K.A and Shalini, S (2011), ANN modeling on prediction of biosorption efficiency of Zea Maize for the removal of Cr(III) and Cr(VI) from wastewater, International Journal of Mathematics Trends and Technology, July/August Issue, pp; 23-29
  • [11]. Cerino-Cordova, F.J; Garcia-Leon, A.M; Garcia-Reyes, R.B; Garza-Gonzalez, M.T; Soto-Regalado, E; Sanchez-Gonzalez, M.N and Quezada-Lopez, I (2011), Response surface methodology for lead biosorption on Aspergillus Tesseus, International Journal of Environmental Science and Technology, vol. 8(4), pp; 695-704
  • [12]. Animesh, D. (2013), Modular approach to big data using neural network, unpublished M.Sc. dissertation submitted to the department of computer science, San Jose State University, pp 23.56.
  • [13]. Mariadas, K.; Kalyani, G.; Joga, H.R.; Kumar, P. Y and King, P., (2012), The removal and equilibrium studies of cadmium by natural clay as adsorbent, International Journal of Scientific Engineering Research, Vol. 3(8), pp 1-6
  • [14]. Krishna, G.B and Susmita, S.G (2006), Adsorption of chromium (VI) from water by clays, Industrial Engineering and Chemical Resource Journal, vol. 45, pp; 7232-7240
  • [15]. Hao, C and Wang, A., (2007), Kinetic and isothermal studies of lead ion adsorption onto polygorskite clay, Journal of Colloid and Interface Science, vol. 307, pp 309 – 316
  • [16]. Badmus, M.A.O.; Audu T.O.K and Anyata, B.U, (2007), Removal of lead ion from industrial wastewaters by activated carbon prepared from periwinkle shells, Turkish Journal of Engineering and Environmental Science, pp; 251 – 263
  • [17]. Gimbert, F.; Morin-Crini, N.; Renault, F.; Badof, P.M and Crini, G., (2008), Adsorption isotherm models for dye removal by cationized starch-based materials in a single component system; Error analysis, Journal of Hazardous Materials, Vol. 157, pp 34-46
  • [18]. Gunay, A.; Arslankaya, E and Tosun, I., (2007), Lead removal from aqueous solution by natural and pretreated clinoptilolite; adsorption equilibrium and kinetics, Journal of Hazardous Materials, Vol. 146, pp 362-371
  • [19]. Hong, Z.; Donghong, L.; Yan, Z.; Shuping, L., and Zhe, L., (2009), Sorption isotherm and kinetic modeling of aniline on Cr-bentonite, Journal of Hazardous Materials, vol. 167, pp 141 – 147
  • [20]. I.R. Ilaboya; E.O. Oti; G.O. Ekoh and L.O. Umukoro (2013); Performance of activated carbon from cassava peels for the treatment of effluent wastewater, Iranica Journal of Energy & Environment (IJEE), an Official Peer Reviewed Journal of Babol Noshirvani University of Technology, vol. 4 (4), pp: 361-375
  • [21]. Abdullah, A.H; Anuark, P; Zulkarnain, Z; Mohd, Z.H; Dzulkefly, K; Faujan, A and Ong, S.W (2001), Preparation and characterization of activated carbon from gelam wood bark (Melaleuca Cajuputi), Malaysian Journal of Analytical Science, vol. 7(1), pp; 65-68
  • [22]. Arenas, L.T; Vaghetti, J.C.P; Moro, C.C; Lima, E.C; Benvenutti, E.V and Costa, T.M.H (2004), Dabco/silica sol-gel hybrid material; the influence of the morphology on the CdCl2 adsorption capacity, Materials Letters, vol. 58 pp; 895-898

Modelling, Optimization And Prediction Of Sorption Of Pb(II) And Mn(II) Ions From Wastewater Onto Acid Activated Shale Using Adaptive Neuro Fuzzy Inference Systems (ANFIS), Response Surface Methodology (RSM) and Modular Neural Network (MNN)

Year 2020, Volume: 4 Issue: 1, 1 - 22, 27.03.2020

Abstract

Batch experimental technique was employed to evaluate the effects of adsorption variables such as initial metal ion concentration, adsorbent dose, pH, and contact time on the sorption efficiency of Pb(II) and Mn(II) ions onto acid activated shale. To select the input variables with the highest significant contributions towards the sorption of Pb(II) and Mn(II) ions onto acid activated shale, adaptive neuro-fuzzy (ANFIS) was employed. Thereafter, statistical design of experiment (DOE) using central composite design was used to generate the data for modelling and prediction using a modular neural network (MNN). To produce accurate network architecture for prediction, the input data were first normalized to avoid the problems of weight variation. Thereafter, different training algorithm and hidden neurons were selected and tested to ascertain the optimum number of hidden neuron and the best training algorithm that will produce the most accurate network.  The linear coefficient of determination in addition to the mean square error for training and cross-validation was employed as the selection criteria. Results obtained shows that, Levenberg Marquardt Back Propagation training algorithm with 2 hidden neurons in the input and output layer with tangent sigmoid transfer function produced the most accurate prediction network. In addition, the modular neural network gave a strong agreement between the experimental and predicted sorption efficiency of Pb(II) and Mn(II) ions with R2 values of 0.977 and 0.9648 having performance statistics of RMSE (0.03815), NRMSE (0.04097), Max.AE (0.02621), Min.AE (0.00041) and R2 (0.988).

References

  • [1]. Lalvani, S.B.; Wiltowski, T., and Weston, A., (2010), Metal ions removal from wastewater by adsorption, Journal of Engineering Science, Vol. 2, pp 877-879
  • [2]. Ong, S.; Seng, C., and Lim, P., (2007), Kinetics of adsorption of copper (II) and cadmium (II) from aqueous solution on rice husk and modified rice husk, Electronic Journal of Environmental Agriculture and food Chemistry, Vol. 6(2), pp 1764-1774.
  • [3]. Kumar, N.K; Reddy, D.S.R and Venkateswarlu, P (2010), Application of response surface methodology for optimization of chromium biosorption from aqueous solution onto Syzigium Cumini (Java) seed powder, Microbial and Biochemical Technology, vol. 2(1), pp; 020-027
  • [4]. Lima, E.C; Betina, R; Vaghetti, J.C.P; Brasil, J.L; Nathalia, M.S; Dos-Santos Jr., A.A; Pavan, F.A; Silvio, L.P.D; Edilson, V.B and Da-Silva, E.A (2007), Adsorption of Cu(II) on Araucaria Augustifolia wastes; determination of the optimal conditions by statistical design of experiment, Journal of Hazardous Materials, vol. 140(1), pp; 211-220
  • [5]. Lin, S. H., and Juang, R.S., (2002), Heavy metal removal from water by sorption using surfactant-modified montmorillonite, Journal of Hazardous Materials, vol. B92, pp 315 – 322
  • [6]. Weng, C.H; Tsai, C.Z; Chu, S.H and Sharma, Y.C., (2007), Adsorption characteristics of copper (II) onto spent activated clay, Separation Purification Technology Journal, vol. 54, pp; 187-197
  • [7]. Sinan, M.T; Beytullah, E and Asude, A (2011), Prediction of adsorption efficiency for the removal of Ni(II) ions by zeolite using artificial neural network (ANN) approach, Fresenius Environmental Bulletin, vol. 20(12), pp; 3158-3165
  • [8]. Mohammed, Y; Farahnaz, E.B; Sepideh, K.B; Bahador, D.J; Soraya, H; Mohammad, R.M and Lugman, A.C (2013), Removal of Ni(II) from aqueous solution by an electric arc furnace slag using artificial neural network (ANN) approach, Advance in Environmental Biology, vol. 7(9), pp; 2303-2310
  • [9]. Abdoliman, A; Ali, A.A and Fatemeh, A (2013), A study of cadmium removal from aqueous solution by sunflower powder and its modeling using artificial neural network (ANN), Iranian Journal of Health Sciences, vol. 1(3), pp; 28-34
  • [10]. Abhishek, K; Kumar, R.R; Jyoti, K.A and Shalini, S (2011), ANN modeling on prediction of biosorption efficiency of Zea Maize for the removal of Cr(III) and Cr(VI) from wastewater, International Journal of Mathematics Trends and Technology, July/August Issue, pp; 23-29
  • [11]. Cerino-Cordova, F.J; Garcia-Leon, A.M; Garcia-Reyes, R.B; Garza-Gonzalez, M.T; Soto-Regalado, E; Sanchez-Gonzalez, M.N and Quezada-Lopez, I (2011), Response surface methodology for lead biosorption on Aspergillus Tesseus, International Journal of Environmental Science and Technology, vol. 8(4), pp; 695-704
  • [12]. Animesh, D. (2013), Modular approach to big data using neural network, unpublished M.Sc. dissertation submitted to the department of computer science, San Jose State University, pp 23.56.
  • [13]. Mariadas, K.; Kalyani, G.; Joga, H.R.; Kumar, P. Y and King, P., (2012), The removal and equilibrium studies of cadmium by natural clay as adsorbent, International Journal of Scientific Engineering Research, Vol. 3(8), pp 1-6
  • [14]. Krishna, G.B and Susmita, S.G (2006), Adsorption of chromium (VI) from water by clays, Industrial Engineering and Chemical Resource Journal, vol. 45, pp; 7232-7240
  • [15]. Hao, C and Wang, A., (2007), Kinetic and isothermal studies of lead ion adsorption onto polygorskite clay, Journal of Colloid and Interface Science, vol. 307, pp 309 – 316
  • [16]. Badmus, M.A.O.; Audu T.O.K and Anyata, B.U, (2007), Removal of lead ion from industrial wastewaters by activated carbon prepared from periwinkle shells, Turkish Journal of Engineering and Environmental Science, pp; 251 – 263
  • [17]. Gimbert, F.; Morin-Crini, N.; Renault, F.; Badof, P.M and Crini, G., (2008), Adsorption isotherm models for dye removal by cationized starch-based materials in a single component system; Error analysis, Journal of Hazardous Materials, Vol. 157, pp 34-46
  • [18]. Gunay, A.; Arslankaya, E and Tosun, I., (2007), Lead removal from aqueous solution by natural and pretreated clinoptilolite; adsorption equilibrium and kinetics, Journal of Hazardous Materials, Vol. 146, pp 362-371
  • [19]. Hong, Z.; Donghong, L.; Yan, Z.; Shuping, L., and Zhe, L., (2009), Sorption isotherm and kinetic modeling of aniline on Cr-bentonite, Journal of Hazardous Materials, vol. 167, pp 141 – 147
  • [20]. I.R. Ilaboya; E.O. Oti; G.O. Ekoh and L.O. Umukoro (2013); Performance of activated carbon from cassava peels for the treatment of effluent wastewater, Iranica Journal of Energy & Environment (IJEE), an Official Peer Reviewed Journal of Babol Noshirvani University of Technology, vol. 4 (4), pp: 361-375
  • [21]. Abdullah, A.H; Anuark, P; Zulkarnain, Z; Mohd, Z.H; Dzulkefly, K; Faujan, A and Ong, S.W (2001), Preparation and characterization of activated carbon from gelam wood bark (Melaleuca Cajuputi), Malaysian Journal of Analytical Science, vol. 7(1), pp; 65-68
  • [22]. Arenas, L.T; Vaghetti, J.C.P; Moro, C.C; Lima, E.C; Benvenutti, E.V and Costa, T.M.H (2004), Dabco/silica sol-gel hybrid material; the influence of the morphology on the CdCl2 adsorption capacity, Materials Letters, vol. 58 pp; 895-898
There are 22 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

İdowu Ilaboya 0000-0002-8982-7404

Osadolor Izinyon This is me

Publication Date March 27, 2020
Published in Issue Year 2020 Volume: 4 Issue: 1

Cite

IEEE İ. Ilaboya and O. Izinyon, “Modelling, Optimization And Prediction Of Sorption Of Pb(II) And Mn(II) Ions From Wastewater Onto Acid Activated Shale Using Adaptive Neuro Fuzzy Inference Systems (ANFIS), Response Surface Methodology (RSM) and Modular Neural Network (MNN)”, IJESA, vol. 4, no. 1, pp. 1–22, 2020.

ISSN 2548-1185
e-ISSN 2587-2176
Period: Quarterly
Founded: 2016
Publisher: Nisantasi University
e-mail:ilhcol@gmail.com