相关实验视频

Updated: Feb 28, 2026

Quasistatic Mechanical Testing for Computer-Aided Design and Manufacturing Occlusal Veneers Cemented to Milled Dentin Analog Material
07:42

Quasistatic Mechanical Testing for Computer-Aided Design and Manufacturing Occlusal Veneers Cemented to Milled Dentin Analog Material

Published on: December 20, 2024

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用高斯过程回归和贝叶斯优化预测和优化牙科树脂复合材料的粘度

Tomoki Kohno1, Naoya Funayama1, Linghao Xiao1

  • 1Joint Research Laboratory of Advanced Functional Materials Science, Graduate School of Dentistry, The University of Osaka, 1-8 Yamadaoka, Suita, Osaka 565-0871, Japan.

Dental materials : official publication of the Academy of Dental Materials
|February 26, 2026
PubMed
概括

机器学习,使用高斯过程回归 (GPR) 和贝叶斯优化 (BO),准确地预测和优化树脂复合材料粘度. 这种数据驱动的方法提高了牙科材料处理特性,用于临床使用.

关键词:
贝叶斯优化的贝叶斯优化高斯过程回归的高斯过程回归.机器学习是机器学习.树脂复合材料 树脂复合材料类风病学 类风病学 类风病学优化粘度优化 粘度优化

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