Artificial neural network for modelling the removal of pollutants: A review
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Creator 1. Siti Fatimah
2. Wiharto
Title Artificial neural network for modelling the removal of pollutants: A review
Publisher Faculty of Engineering, Khon Kaen University
Publication Year 2563
Journal Title Engineering and Applied Science Research
Journal Vol. 47
Journal No. 3
Page no. 339-347
Keyword Review, Pollutants, Removal, Degradation, Artificial neural network
URL Website https://www.tci-thaijo.org/index.php/easr/index
Website title Engineering and Applied Science Research
ISSN 2539-6161
Abstract Modeling of pollutant degradation using artificial neural networks (ANN) has been done well. The techniques used to model degradation vary. This literature review was done to examine the development of the use of ANN modeling from year to year. It will provide an overview of predictive studies from a degradation treatmentcondition that will produce optimal conditions. These conditionswill be supportedby experimental data so that costsand time can be reduced atlaboratory scale. Some relevant techniques include separation methods, coagulation, advanced oxidation processes, andchemical oxidation. The algorithmic approaches used are ANN-LM, ANN-BP, ANN-BP (SCG),andANN-BFGS. Modelling using ANN hasveryhighpotential for furtherdevelopment.The perfomance indicator of anANN method isastrong coefficientofdetermination(R2), with good RMSE, MAPE, and MSEvalues.
Engineering and Applied Science Research

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