首页|New Machine Learning Study Results from Argonne National Laboratory Described (M achine Learning Models and Dimensionality Reduction for Prediction of Polymer Pr operties)
New Machine Learning Study Results from Argonne National Laboratory Described (M achine Learning Models and Dimensionality Reduction for Prediction of Polymer Pr operties)
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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).
LemontIllinoisUnited StatesNorth a nd Central AmericaCyborgsDimensionality ReductionEmerging TechnologiesMa chine LearningArgonne National Laboratory
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