首页|Shanghai Jiao Tong University Reports Findings in Machine Learning (Refining hyd rogel-based sorbent design for efficient toxic metal removal using machine learn ing-Bayesian optimization)
Shanghai Jiao Tong University Reports Findings in Machine Learning (Refining hyd rogel-based sorbent design for efficient toxic metal removal using machine learn ing-Bayesian optimization)
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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 originating from Shanghai, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Hydrogelbased sorbe nts show promise in the removal of toxic metals from water. However, optimizing their performance through conventional trial-and-error methods is both costly an d challenging due to the inherent high-dimensional parameter space associated wi th complex condition combinations.”
ShanghaiPeople’s Republic of ChinaAs iaAlcoholsCyborgsEmerging TechnologiesHydrogelMachine LearningOrgani c ChemicalsPolyethylene Glycols
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