Robotics & Machine Learning Daily News2024,Issue(Sep.23) :57-57.

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)

Robotics & Machine Learning Daily News2024,Issue(Sep.23) :57-57.

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)

扫码查看

Abstract

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.”

Key words

Shanghai/People’s Republic of China/As ia/Alcohols/Cyborgs/Emerging Technologies/Hydrogel/Machine Learning/Organi c Chemicals/Polyethylene Glycols

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文