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NewsRx编辑在杭州报道，研究称，“在实地”在catalyst设计中,机器学习正受到越来越多的关注,特别是在数据处理的场合是有限的。面对这种挑战，我们开发了一种神经网络模型来增强预测能力通过仔细选择CA Talyst描述符和特征工程，以预测精度乙炔半氢化反应的转化率和选择性。
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 newsreporting out of Hangzhou, People’s R epublic of China, by NewsRx editors, research stated, “In the fieldof catalyst design, machine learning is gaining significant attention, especially in situati ons where datais limited. Facing this challenge, we have developed a neural net work model that enhances predictiveaccuracy through the careful selection of ca talyst descriptors and feature engineering, aiming to predictthe conversion rat e and selectivity of the acetylene semi-hydrogenation reaction.”
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