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-机器学习的最新研究结果已经发表。据新闻报道来自西维尔吉尼亚的摩根敦，由NewsRx记者报道，研究表明，“数据驱动的介绍了用机器学习g(ML)模型预测常用油气混合物层流火焰速度(LFS)其主要优点是在各种温度下使用方便、快捷，单一和多化合物燃料的压力、当量比和各种组成。具体地说，结合(Ⅰ)Cantera，一个用于模拟化学动力学、热力学的开源软件，(ⅱ)新建立的回归学习模型能够预测用于各种燃料和燃料混合物的LFS，包括氢、烃如甲烷的LFS，乙烷、丙烷以及锂离子电池的可燃性气体。
Abstract
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 newsoriginating from Morgantown, West Vir ginia, by NewsRx correspondents, research stated, “A data-drivenmachine learnin g (ML) model for predicting laminar flame speeds (LFS) of common fuel-air mixtur es isdeveloped, with a major advantage of being convenient and prompt to be use d at various temperatures,pressures, equivalence ratios and various composition s for both single and multi-compounds fuels. Specifically,combining (ⅰ) Cantera , an open-source software for modeling chemical kinetics, thermodynamics,and tr ansport processes and (ⅱ) the regression learner model, the newly developed mod el is able to predictthe LFS for various fuels and fuel blends, including those of hydrogen, hydrocarbons such as methane,ethane, propane as well as combustib le gases from lithium-ion batteries.”
NETL
NSTL