Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

48
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
48
Structures of Solids02:22

Structures of Solids

14.1K
Solids in which the atoms, ions, or molecules are arranged in a definite repeating pattern are known as crystalline solids. Metals and ionic compounds typically form ordered, crystalline solids. A crystalline solid has a precise melting temperature because each atom or molecule of the same type is held in place with the same forces or energy. Amorphous solids or non-crystalline solids (or, sometimes, glasses) which lack an ordered internal structure and are randomly arranged. Substances that...
14.1K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Re-Evaluating Virtual Reality Manipulation Techniques for Precise Alignment of Complex 3D Objects.

IEEE transactions on visualization and computer graphics·2026
Same author

Three-Dimensional Bubble Fluidics in Architected Porous Media.

ACS applied materials & interfaces·2025
Same author

LatticeAnalytics: Strut-Level Visualization and Inspection of Additively Manufactured Lattice Structures.

IEEE transactions on visualization and computer graphics·2025
Same author

Materials Data Science Ontology(MDS-Onto): Unifying Domain Knowledge in Materials and Applied Data Science.

Scientific data·2025
Same author

Enabling additive manufacturing part inspection of digital twins via collaborative virtual reality.

Scientific reports·2024
Same author

HaloTag-Modified, Ferrocene Labeled Self-Assembled Monolayers for Protein Sensing.

Langmuir : the ACS journal of surfaces and colloids·2024
Same journal

Application of ephrin-B2 loaded glycol chitosan-silk fibroin hydrogel in the treatment of diabetic refractory wounds.

Scientific reports·2026
Same journal

International expert Delphi consensus on thromboprophylaxis in metabolic and bariatric surgery.

Scientific reports·2026
Same journal

Assessing the cross-region knowledge transfer capability of selected deep learning building vectorization methods in the context of available training datasets.

Scientific reports·2026
Same journal

Feasibility and preliminary effects of outdoor versus indoor cognitive-motor therapy in women with Alzheimer's disease: A randomized single-blind pilot study.

Scientific reports·2026
Same journal

Hallmarks of social action in the vocal turn-taking of wild common marmosets (Callithrix jacchus).

Scientific reports·2026
Same journal

Role and mechanism of AOPPs-induced NOX4-mediated ferroptosis in intervertebral disc degeneration.

Scientific reports·2026
查看所有相关文章

相关实验视频

Updated: Jun 24, 2025

Indirect Fabrication of Lattice Metals with Thin Sections Using Centrifugal Casting
08:32

Indirect Fabrication of Lattice Metals with Thin Sections Using Centrifugal Casting

Published on: May 14, 2016

12.5K

使用机器学习加速格子结构的设计.

Aldair E Gongora1, Caleb Friedman2, Deirdre K Newton2

  • 1Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA, 94550, USA. gongora1@llnl.gov.

Scientific reports
|June 13, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了一种机器学习 (ML) 方法,与沙普利增量解释 (SHAP) 结合起来,以高效设计格子结构. 该方法通过解释变量并减少模拟需求,加速发现最佳设计.

更多相关视频

Visualizing Surface T-Cell Receptor Dynamics Four-Dimensionally Using Lattice Light-Sheet Microscopy
09:24

Visualizing Surface T-Cell Receptor Dynamics Four-Dimensionally Using Lattice Light-Sheet Microscopy

Published on: January 30, 2020

8.0K
A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

9.9K

相关实验视频

Last Updated: Jun 24, 2025

Indirect Fabrication of Lattice Metals with Thin Sections Using Centrifugal Casting
08:32

Indirect Fabrication of Lattice Metals with Thin Sections Using Centrifugal Casting

Published on: May 14, 2016

12.5K
Visualizing Surface T-Cell Receptor Dynamics Four-Dimensionally Using Lattice Light-Sheet Microscopy
09:24

Visualizing Surface T-Cell Receptor Dynamics Four-Dimensionally Using Lattice Light-Sheet Microscopy

Published on: January 30, 2020

8.0K
A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

9.9K

科学领域:

  • 工程 工程师 工程师 工程师
  • 材料科学 材料科学 材料科学
  • 计算科学 计算科学

背景情况:

  • 格子结构提供了设计的多功能性,但快速,优化的机械性能设计是具有挑战性的.
  • 越来越多的设计变量导致难以处理的设计空间,需要高效的计算方法.
  • 现有的机器学习 (ML) 方法在模型解释和高效的培训数据策划方面面临挑战.

研究的目的:

  • 为加速格子结构设计开发一个可解释的ML框架.
  • 通过使用ML和可解释性技术来识别影响机械性能的关键设计变量.
  • 为了提高训练数据策划的效率,用于网格设计中的优化任务.

主要方法:

  • 结合基于ML的替代模型与Shapley添加式解释 (SHAP) 进行变量解释.
  • 利用主动学习方法,特别是贝叶斯优化,以高效设计太空探索.
  • 开发了一个集成ML的智能系统,用于设计变量发现和加速.

主要成果:

  • 基于ML的替代模型显示出高预测准确度 (R2 > 0.95).
  • SHAP分析有效地确定了影响格子结构性能的设计变量.
  • 与基于网格的搜索相比,主动学习减少了5倍的模拟需求.

结论:

  • 集成ML和SHAP提供了一个强大的工具来解释网格结构中的设计变量.
  • 积极学习策略显著提高了设计和优化过程的效率.
  • 利用ML的智能设计系统对于加速定制格子结构的开发至关重要.