首页|Chongqing University Reports Findings in Machine Learning (Development and appli cation of an intelligent nitrogen removal diagnosis and optimization framework for WWTPs: Low-carbon and stable operation)
Chongqing University Reports Findings in Machine Learning (Development and appli cation of an intelligent nitrogen removal diagnosis and optimization framework for WWTPs: Low-carbon and stable operation)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating from Chongqing, P eople’s Republic of China, by NewsRx correspondents, research stated, “Optimizin g nitrogen removal is crucial for ensuring the efficient operation of wastewater treatment plants (WWTPs), but it is susceptible to variations in influent condi tions and operational parameter constraints, and conflicts with the energy-savin g and carbon emission reduction goals. To address these issues, this study propo ses a hybrid framework integrating process simulation, machine learning, and mul ti-objective genetic algorithms for nitrogen removal diagnosis and optimization, aiming to predict the total nitrogen in effluent, diagnose nitrogen over-limit risks, and optimize the control strategies.”
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