This study proposes a method for simulating the wastewater treatment process using recurrent neural networks and aims to develop a soft measurement model applicable to the sequencing batch reactor for treating domes-tic wastewater.The model combines the measured values of other easily obtainable variables to achieve real-time monitoring of important water quality indicators in wastewater treatment.By collecting measured data from the domes-tic wastewater treatment unit and comparing it with the model's predicted results,the effectiveness of the model in practical operating environments has been validated.The soft measurement model developed in this study provides an effective and cost-efficient solution for predicting water quality in the SBR process.Through soft measurement of im-portant indicators,operational strategies can be improved,and treatment efficiency can be enhanced,thereby offering a sustainable pathway for wastewater treatment.
维普
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