Artificial neural network and multiple linear regression for modeling sorption of Pb²⁺ ions from aqueous solutions onto modified walnut shell

Neural-based modeling adsorption capacity of metal organic framework materials with application in wastewater treatment

“…The proposed network by ANN capable in prediction of Cd adsorption with high accuracy 77 ANN R 2 Walnut shell-rice husk ratio, calcination duration and temperature Sorption efficiency Adsorption of Cd on Nano-magnetic walnut shell-rice husk 78 ANN, MLR R 2 Treatment time, adsorbent weight, C 0 , solution pH Separation efficiency Adsorption of Pb(II) on carboxylate-functionalized walnut shell (CFWS). Result confirmed ANN model was able to predict the Pb(II) removal more accurately compare to MLR 79 GA-ANN MSE, R 2 No. of adsorbent, solution pH, adsorbent weight, time, and initial content Removal efficiency Adsorption of Cd on natural waste materials (leaves of jackfruit, mango and rubber plants).…”

Application of neural network in metal adsorption using biomaterials (BMs): a review

“…47,63,[96][97][98] The RSM approach is only conned to a quadratic equation; thus ANN-based model offers broader competence to capture the complex and nonlinear behaviour of the metal adsorption process from effluents with a wide spectrum of dependent factors. 57,75,86,99,100 While ANN models for metal remediation call for advanced computing abilities, Narayana et al, 2021 proposed an ANN-based graphical user interface (GUI) for experimentalists or researchers unfamiliar with computation to extract adsorption data for a particular dataset. 85…”

Applications of artificial intelligence in water treatment for optimization and automation of adsorption processes: Recent advances and prospects

“…The adsorption performance of different adsorbents for the removal of Cr(III), Cr(IV), Cu(II), Pb(II), As(III), Zn(II), Cd(II), and Hg(II) by different adsorbents was determined by the using various AI tools, mainly ANN [53][54][55][56][57][58][59][60][61] Some studies also employed the AI tools to assess the performance of adsorption for the simultaneous removal of multiple metals from aqueous phase [62] 13]. Studies also evaluated the performance of various adsorbents for the removal of dyes in a continuous system using AI tools [63].…”