Artificial Neural Network Modeling of Cr(VI) Biosorption from Aqueous Solutions
作者： Farzaneh Mohammadi , Zeynab Yavari , Somaye Rahimi , Majid Hashemi
DOI: 10.3103/S1063455X19040039
关键词:
摘要: Artificial neural network (ANN) model was applied for predicting the biosorption capacity of excess municipal wastewater sludge hexavalent chromium (Cr(VI)) ions from aqueous solution. The effects initial concentration (5 to 90 mg/L), adsorbent dosage (2 10 g/L), pH 8), agitation speed (50 200 rpm) and time 480 min) were investigated. maximum amount removal about 96% in optimum conditions. experimental results simulated using ANN model. Levenberg-Marquardt algorithm used training this with tangent sigmoid as transfer function at hidden output layer 13 1 neurons, respectively. successfully predicted Cr(VI) capacity. average mean square error is 0.00401 correlation coefficient between rate 0.9833.
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sci-hub.se 参考文章(20)
Andrew Eaton, A.E. Greenberg, Lenore S. Clesceri, Standard methods for the examination of water and wastewater Published in <b>1998</b> in Washington DC) by American public health association. ,(1992)
Yuyi Yang, Guan Wang, Bing Wang, Zeli Li, Xiaoming Jia, Qifa Zhou, Yuhua Zhao, Biosorption of Acid Black 172 and Congo Red from aqueous solution by nonviable Penicillium YW 01: kinetic study, equilibrium isotherm and artificial neural network modeling. Bioresource Technology. ,vol. 102, pp. 828- 834 ,(2011) , 10.1016/J.BIORTECH.2010.08.125
Maomin Shi, Zhonghong Li, Yahong Yuan, Tianli Yue, Jianlong Wang, Ronghua Li, Jinghong Chen, In situ oxidized magnetite membranes from 316L porous stainless steel via a two-stage sintering process for hexavalent chromium [Cr(VI)] removal from aqueous solutions Chemical Engineering Journal. ,vol. 265, pp. 84- 92 ,(2015) , 10.1016/J.CEJ.2014.12.018
Y.R. Ding, Y.J. Cai, P.D. Sun, B. Chen, The Use of Combined Neural Networks and Genetic Algorithms for Prediction of River Water Quality Journal of Applied Research and Technology. ,vol. 12, pp. 493- 499 ,(2014) , 10.1016/S1665-6423(14)71629-3
A.K. Giri, R.K. Patel, S.S. Mahapatra, Artificial neural network (ANN) approach for modelling of arsenic (III) biosorption from aqueous solution by living cells of Bacillus cereus biomass Chemical Engineering Journal. ,vol. 178, pp. 15- 25 ,(2011) , 10.1016/J.CEJ.2011.09.111
Qian-Qian Zhong, Qin-Yan Yue, Qian Li, Bao-Yu Gao, Xing Xu, Removal of Cu(II) and Cr(VI) from wastewater by an amphoteric sorbent based on cellulose-rich biomass Carbohydrate Polymers. ,vol. 111, pp. 788- 796 ,(2014) , 10.1016/J.CARBPOL.2014.05.043
Ihsan Ullah, Raziya Nadeem, Munawar Iqbal, Qaisar Manzoor, None, Biosorption of chromium onto native and immobilized sugarcane bagasse waste biomass Ecological Engineering. ,vol. 60, pp. 99- 107 ,(2013) , 10.1016/J.ECOLENG.2013.07.028
Hala Ahmed Hegazi, Removal of heavy metals from wastewater using agricultural and industrial wastes as adsorbents HBRC Journal. ,vol. 9, pp. 276- 282 ,(2013) , 10.1016/J.HBRCJ.2013.08.004
S. Chakraborty, J. Dasgupta, U. Farooq, J. Sikder, E. Drioli, S. Curcio, Experimental analysis, modeling and optimization of chromium (VI) removal from aqueous solutions by polymer-enhanced ultrafiltration Journal of Membrane Science. ,vol. 456, pp. 139- 154 ,(2014) , 10.1016/J.MEMSCI.2014.01.016
M. Shanmugaprakash, V. Sivakumar, Development of experimental design approach and ANN-based models for determination of Cr(VI) ions uptake rate from aqueous solution onto the solid biodiesel waste residue. Bioresource Technology. ,vol. 148, pp. 550- 559 ,(2013) , 10.1016/J.BIORTECH.2013.08.149