摘要
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-机器学习的研究结果将在一份新报告中讨论。根据NewsRx记者从加拿大Hami Lton发回的新闻报道，研究称，“碳排放”材料表面具有许多活性位点和功能,可以吸引大量的材料用于各种气体吸附的固体吸附剂。本研究旨在预测最佳甲烷吸收量，吸附能(E AD)和吸附剂可通过神经、回归、分类等多种技术实现ML-DFT，以及Unifo RM流形逼近和投影(UMAP)。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Machine Learning are discussed in a new report. According tonews reporting originating from Hami lton, Canada, by NewsRx correspondents, research stated, “Carbonmaterials posse ss active sites and functionalities on the surface that can attract prominent in terest assolid adsorbents for diverse gas adsorption. This study aimed to predi ct the optimized methane uptake,adsorption energy (E ad), and adsorbent redisco very through multitechniques of neural, regression, classifierML-DFT, and Unifo rm Manifold Approximation and Projection (UMAP).”
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