首页|University of Michigan Reports Findings in Machine Learning (Machine Learning Pr edictions of Methane Storage in MOFs: Diverse Materials, Multiple Operating Cond itions, and Reverse Models)
University of Michigan Reports Findings in Machine Learning (Machine Learning Pr edictions of Methane Storage in MOFs: Diverse Materials, Multiple Operating Cond itions, and Reverse Models)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
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 reporting originating from Ann Arbor, M ichigan, by NewsRx correspondents, research stated, “A machine learning (ML) mod el is developed for predicting useable methane (CH) capacities in metal-organic frameworks (MOFs). The model applies to a wide variety of MOFs, including those with and without open metal sites, and predicts capacities for multiple pressure swing conditions.”
Ann ArborMichiganUnited StatesNort h and Central AmericaAlkanesCyborgsEmerging TechnologiesMachine LearningMethane
NETL
NSTL
