https://www.selleckchem.com/products/tr-107.html
The efficiency of heavy metal in biofilm reactors depends on absorption process parameters, and those relationships are complicated. This study explores artificial neural networks (ANNs) feasibility to correlate the biofilm reactor process parameters with absorption efficiency. The heavy metal removal and turbidity were modeled as a function of five process parameters, namely pH, temperature(°C), feed fluml/min), substrate flow(ml/min), and hydraulic retention time(h). We developed a standalone ANN software for predicting and analyzing
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