首页|Nanjing University Reports Findings in Machine Learning (Machine learning modeli ng of fluorescence spectral data for prediction of trace organic contaminant rem oval during UV/H2O2 treatment of wastewater)
Nanjing University Reports Findings in Machine Learning (Machine learning modeli ng of fluorescence spectral data for prediction of trace organic contaminant rem oval during UV/H2O2 treatment of wastewater)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting originating from Nanjing, Peo ple’s Republic of China, by NewsRx correspondents, researchstated, “Dynamic fee dback of the removal performance of trace organic contaminants (TrOCs) is essential towards economical advanced oxidation processes (AOPs), whereas the correspo nding quick-responsefeedback methods have long been desired. Herein, machine le arning (ML) multi-target regression randomforest (MORF) models were developed b ased on the fluorescence spectra to predict the removal of TrOCsduring UV/HO tr eatment of municipal secondary effluent as a typical AOP.”
NanjingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine Learning
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