Robotics & Machine Learning Daily News2024,Issue(Dec.6) :143-143.

Investigators at Texas A&M University Discuss Findings in Machine L earning (Generative Inverse Design of Metamaterials With Functional Responses By Interpretable Learning)

德克萨斯农工大学的研究人员讨论机器学习的发现(通过可解释学习对具有功能反应的超材料进行生成性逆设计)

Robotics & Machine Learning Daily News2024,Issue(Dec.6) :143-143.

Investigators at Texas A&M University Discuss Findings in Machine L earning (Generative Inverse Design of Metamaterials With Functional Responses By Interpretable Learning)

德克萨斯农工大学的研究人员讨论机器学习的发现(通过可解释学习对具有功能反应的超材料进行生成性逆设计)

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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-机器学习的新研究是一篇报道的主题。据新闻报道来自德克萨斯州College Stat Ion的报道,由NewsRx记者报道,研究称,“超材料”在不同的条件下(例如,基于波的响应),函数响应可以表现出不同的特性响应或变形引起的性质变化。这项工作增加了这类零件的快速反求设计超材料满足目标的定性功能行为,由于其难易性和非唯一的解决方案。 ”

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsreporting originating from College Stat ion, Texas, by NewsRx correspondents, research stated, “Metamaterialswith funct ional responses can exhibit varying properties under different conditions (e.g., wave-basedresponses or deformation-induced property variation). This work addr esses rapid inverse design of suchmetamaterials to meet target qualitative func tional behaviors, a challenge due to its intractability andnonunique solutions. ”

Key words

College Station/Texas/United States/N orth and Central America/Machine Learning/Texas A&M University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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