Abstract
The research presented in this article refers to the optimization of oxygen requirement in biological wastewater treatment using machine learning (ML) techniques with the highest efficiency of the process. The treatment technology of wastewater treatment plant consists of sequential biological reactor with nutrient removal. The analysis is based on the daily data over a period of 2 years, influent, respectively effluent wastewater characteristics, wastewater flow rate and concentration of oxygen in biological reactor. Octave software was used to build the model and it was obtained an accuracy of 85%.
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