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A predictive model based on artificial neural networks (ANNs) for modeling the primary settling tanks (PSTs) behavior in wastewater treatment plants was developed in this study. Two separated ANNs were built using input data, raw wastewater characteristics, and operating conditions. The output data from the ANNs consisted of the total suspended solids (TSS) concentration and the chemical oxygen demand (COD) as predictions of PSTs' typical effluent parameters. Data from a large-scale wastewaterdoi:10.2166/wst.2022.186 pmid:35771057 fatcat:lc5yjmojbzgj3dum75j7gwotaa