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-调查人员发布马学习新报告。根据消息来源来自俄克拉何马州诺曼，由NewsRx C或受访者撰写，研究称，“电火花加工”(EDM)是一种以在坚硬材料中塑造复杂几何形状而闻名的symanex工艺，尽管o由于大量的实验测试，优化其性能是昂贵的。我们在引见EDMNet，用于预测电火花加工性能的新型机器学习(ML)基准框架带电极振动的粉末混合放电加工(PM-EDM)，可就地在线EDM过程的监测"。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Ma chine Learning. According to news originatingfrom Norman, Oklahoma, by NewsRx c orrespondents, research stated, “Electrical discharge machining(EDM) is a compl ex process renowned for shaping intricate geometries in hard materials, though optimizing its performance is costly due to extensive experimental testing. We in troduce EDMNet, anovel machine learning (ML) benchmark framework for predicting EDM performance, specifically in smartpowder mixed-electrical discharge machin ing (PM-EDM) with electrode vibration, enabling in situ, onlinemonitoring of th e EDM process.”
NETL
NSTL