Robotics & Machine Learning Daily News2024,Issue(Nov.15) :91-91.

University of Florida Reports Findings in Machine Learning (Machine Learning-ena bled Parameterization Scheme for Aerodynamic Shape Optimization of Wind-sensitiv e Structures: A-proof-ofconcept Study)

佛罗里达大学报告机器学习的发现(风敏感结构气动形状优化的机器学习-可编程参数化方案:概念验证研究)

Robotics & Machine Learning Daily News2024,Issue(Nov.15) :91-91.

University of Florida Reports Findings in Machine Learning (Machine Learning-ena bled Parameterization Scheme for Aerodynamic Shape Optimization of Wind-sensitiv e Structures: A-proof-ofconcept Study)

佛罗里达大学报告机器学习的发现(风敏感结构气动形状优化的机器学习-可编程参数化方案:概念验证研究)

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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-调查人员发布马学习的新报告。根据新闻报道来自佛罗里达州盖恩斯维尔,由NewsRx记者报道,研究称,“空气动力学形状”优化是提高风敏感结构性能的重要手段。然而,形状参数化作为气动外形优化的第一步,在很大程度上依赖于关于经验判断。

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 reportingoriginating from Gainesville, Florid a, by NewsRx correspondents, research stated, “Aerodynamic shapeoptimization is very useful for enhancing the performance of wind-sensitive structures. However , shapeparameterization, as the first step in the pipeline of aerodynamic shape optimization, still heavily dependson empirical judgment.”

Key words

Gainesville/Florida/United States/Nor th and Central America/Cyborgs/Emerging Technologies/Machine Learning/Univer sity of Florida

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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