首页|Beijing University of Technology Reports Findings in Machine Learning (Reliable assessment and prediction of moderate preoxidation of sodium hypochlorite for al gae-laden water treatment)
Beijing University of Technology Reports Findings in Machine Learning (Reliable assessment and prediction of moderate preoxidation of sodium hypochlorite for al gae-laden water treatment)
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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 from Beijing, People’s Republ ic of China, by NewsRx journalists, research stated, “Chemical moderate preoxida tion for algae-laden water is an economical and prospective strategy for control ling algae and exogenous pollutants, whereas it is constrained by a lack of effe ctive on-line evaluation and quickresponse feedback method. Herein, excitation- emission matrix parallel factor analysis (EEM-PARAFAC) was used to identify cyan obacteria fluorophores after preoxidation of sodium hypochlorite (NaClO) at Exci tation/Emission wavelength of 260(360)/450 nm, based on which the algal cell int egrity and intracellular organic matter (IOM) release were quantitatively assess ed.”
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