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The use of artificial neural networks (ANN) for modeling of adsorption of Cr(Ⅵ) ions

机译:人工神经网络(ANN)用于Cr(Ⅵ)离子吸附的建模

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摘要

In this study, an artificial neural network (ANN) based techniques is applied for the prediction of the percentage removal of Cr(Ⅵ) ions from aqueous solution using eight different natural biosorbents. The effects of operating parameters such as initial pH, initial Cr(Ⅵ) ion concentration, adsorbent dosages, and contact time are studied to optimize the conditions for maximum removal of Cr(Ⅵ) ions. The ANN with a single hidden layer trained with Leven-berg-Marquardt algorithm predicted the percentage removal of Cr(Ⅵ) ions from aqueous solution accurately.
机译:在这项研究中,基于人工神经网络(ANN)的技术被用于预测使用八种天然生物吸附剂从水溶液中去除Cr(Ⅵ)离子的百分比。研究了初始pH,初始Cr(Ⅵ)离子浓度,吸附剂剂量和接触时间等操作参数的影响,以优化最大去除Cr(Ⅵ)离子的条件。用Levenberg-Marquardt算法训练的具有单个隐藏层的ANN可以准确预测水溶液中Cr(Ⅵ)离子的去除率。

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