Study Results from National Center for Scientific Research (CNRS) in the Area of Machine Learning Reported (Unsupervised Machine Learning Classification for Acc elerating Fe2 Multiscale Fracture Simulations)
Study Results from National Center for Scientific Research (CNRS) in the Area of Machine Learning Reported (Unsupervised Machine Learning Classification for Acc elerating Fe2 Multiscale Fracture Simulations)
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-一项关于机器学习的新研究现在可用。根据新闻报道由NewsRx记者从法国Marne La Vallee发出的研究报告称，“一种方法”本文提出了一种加速非均质准脆性材料多尺度模拟的方法各向异性损伤响应。目前的技术采用无监督机器学习分类基于k-means聚类的FE2宏网格积分点选择跟踪冗余微非线性对象避免不必要的代表体元(RVE)计算。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Machine Learning is now available. According to news reportingoriginating from Marne la Vallee, France , by NewsRx correspondents, research stated, “An approachis proposed to acceler ate multiscale simulations of heterogeneous quasi-brittle materials exhibiting a nanisotropic damage response. The present technique uses unsupervised machine l earning classificationbased on k-means clustering to select integration points in the macro mesh within an FE2 2 strategyto track redundant micro nonlinear pr oblems and to avoid unnecessary Representative Volume Element(RVE) calculations .”
Key words
Marne la Vallee/France/Europe/Cyborgs/Emerging Technologies/Machine Learning/National Center for Scientific Resear ch (CNRS)
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