首页|New Machine Learning Data Have Been Reported by Investigators at Chinese Academy of Sciences (Parametric Analysis of Co2 Hydrogenation Via Fischer-tropsch Synth esis: a Review Based On Machine Learning for Quantitative Assessment)
New Machine Learning Data Have Been Reported by Investigators at Chinese Academy of Sciences (Parametric Analysis of Co2 Hydrogenation Via Fischer-tropsch Synth esis: a Review Based On Machine Learning for Quantitative Assessment)
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 DailyNews Daily News – Current study results on Machine Learn ing have been published. According to newsreporting from Beijing, People’s Repu blic of China, by NewsRx journalists, research stated, “This reviewfocuses on t he parametric impacts upon conversion and selectivity during CO2 hydrogenation v ia Fischer-Tropsch (FT) synthesis using iron-based catalyst to provide quantitat ive evaluation. Using all collecteddata from reported literatures as training d ataset via artificial neural networks (ANNs) in TensorFlow,three categorized pa rameters (namely: operational, catalyst informatic and mass transfer) were deplo yedto assess their impacts upon conversions (CO2) and selectivity.”
BeijingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningChinese Academy of Sciences
NETL
NSTL
