文章基本信息

标题：Adsorption of tetracycline antibiotic onto modified zeolite: Experimental investigation and modeling
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作者：Maryam Dolatabadi ; Marjan Mehrabpour ; Morteza Esfandyari 等
期刊名称：MethodsX
印刷版ISSN：2215-0161
电子版ISSN：2215-0161
出版年度：2020
卷号：7
页码：1-9
DOI：10.1016/j.mex.2020.100885
语种：English
出版社：Elsevier
摘要：AbstractArtificial Neural Networks (ANNs) model and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used to estimate and predict the removal efficiency of tetracycline (TC) using the adsorption process from aqueous solutions. The obtained results demonstrated that the optimum condition for removal efficiency of TC were 1.5 g L−1modified zeolite (MZ), pH of 8.0, initial TC concentration of 10.0 mg L−1, and reaction time of 60 min. Among the different back-propagation algorithms, the Marquardt–Levenberg learning algorithm was selected for ANN Model. The log sigmoid transfer function (log sig) at the hidden layer with ten neurons in the first layer and a linear transfer function were used for prediction of the removal efficiency. Accordingly, a correlation coefficient, mean square error, and absolute error percentage of 0.9331, 0.0017, and 0.56% were obtained for the total dataset, respectively. The results revealed that the ANN has great performance in predicting the removal efficiency of TC.•ANNs used to estimate and predict tetracycline antibiotic removal using the adsorption process from aqueous solutions.•The model's predictive performance evaluated by MSE, MAPE, and R2.Graphical abstractThe architecture of the ANFIS model for predicting the removal efficiency of TC.Display Omitted
关键词：Artificial Neural Network;Zeolite;Antibiotic;Tetracycline