Robotics & Machine Learning Daily News2024,Issue(Nov.1) :41-41.

New Machine Learning Study Results from Argonne National Laboratory Described (M achine Learning Models and Dimensionality Reduction for Prediction of Polymer Pr operties)

Robotics & Machine Learning Daily News2024,Issue(Nov.1) :41-41.

New Machine Learning Study Results from Argonne National Laboratory Described (M achine Learning Models and Dimensionality Reduction for Prediction of Polymer Pr operties)

扫码查看

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news reporting originating from Lemont, Ill inois, by NewsRx correspondents, research stated, “Accurate prediction of block polymer properties as a function of monomer sequence is necessary for better mat erial development. The number of permutations of chemistry and sequence is nearl y infinite, and new methods are needed to predict and engineer properties as a f unction of molecular structure.” Funders for this research include United States Department of Energy (DOE), Unit ed States Department of Energy (DOE).

Key words

Lemont/Illinois/United States/North a nd Central America/Cyborgs/Dimensionality Reduction/Emerging Technologies/Ma chine Learning/Argonne National Laboratory

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