首页|Studies from Hebei University of Technology Yield New Data on Machine Learning ( Machine Learning Predict the Degradation Efficiency of Aqueous Refractory Organi c Pollutants By Ultrasoundbased Advanced Oxidation Processes)
Studies from Hebei University of Technology Yield New Data on Machine Learning ( Machine Learning Predict the Degradation Efficiency of Aqueous Refractory Organi c Pollutants By Ultrasoundbased Advanced Oxidation Processes)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Machine Learning are discussed in a new report. According to news reporting originating in Tianji n, People’s Republic of China, by NewsRx journalists, research stated, “Ultrasou nd based advanced oxidation processes (AOPs) are effective for removing refracto ry organic pollutants by generating reactive species. Machine learning (ML) can systematically provide an excellent opportunity to determine the relationship be tween feature variables and output variables through large amounts of data, ther eby reducing the need for experimental measurements.” Funders for this research include Natural Science Foundation of Hebei Province, Doctoral Research Foundation of Changzhi Medical College.
TianjinPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningHebei University of Technol ogy
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