首页|Xi'an University of Architecture and Technology Reports Findings in Machine Lear ning (Intelligent optimal control model of selection pressure for rapid culture of aerobic granular sludge based on machine learning and simulated annealing ... )
Xi'an University of Architecture and Technology Reports Findings in Machine Lear ning (Intelligent optimal control model of selection pressure for rapid culture of aerobic granular sludge based on machine learning and simulated annealing ... )
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Machine Learning is the subject o f a report. According to news reporting from Xi'an, People's Republic of China, by NewsRx journalists, research stated, "Aerobic Granular Sludge (AGS) has advan tages over Activated sludge (AS) but faces challenges with long granulation peri ods. In this study, a novel grey-box model is devised to optimize the cultivatio n of AGS to shorten the formation time." The news correspondents obtained a quote from the research from the Xi'an Univer sity of Architecture and Technology, "This model is based on an existing white-b ox model. The modeling process starts with the application of four sensitivity a nalysis methods to assess the 12 model metrics selected. Subsequently, 12 predic tion models were constructed by combining the six Machine learning (ML) algorith ms and integrated algorithms, with the best performance selected (R = 0.98). Fin ally, an AGS selection pressure planning model was designed in conjunction with a simulated annealing (SA) algorithm to guide AGS training. The results demonstr ate that AGS formation could be achieved within four days under the model's opti mal control."
Xi'anPeople's Republic of ChinaAsiaAlgorithmsCyborgsEmerging TechnologiesMachine Learning
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