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-关于机器学习的详细数据已经呈现。根据消息来源来自中华人民共和国山东，由NewsRx记者报道，研究称，“准备工作”乙酰丙酸(LA)氢化γ-v警报内酯是绿色、高效、经济的,但传统的催化剂选择和优化方法效率低、成本高,不能满足人们的满足化工行业的发展需要。为此，我们进行了一项新的研究，以开发一个预测LA转化率和γ-戊内酯产率的机器学习框架选择和优化。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news originatingfrom Shandong, People’s Republic of China, by NewsRx correspondents, research stated, “The preparationof gamma-v alerolactone by levulinic acid (LA) hydrogenation is green, efficient, and econo mical, but thetraditional catalyst selection and optimization methods have low efficiency and high cost, which cannotmeet the development needs of the chemica l industry. To this end, we conducted new research to develop amachine learning framework to predict LA conversion and gamma-valerolactone yield, accelerating catalystselection and optimization.”
NETL
NSTL