z-logo
open-access-imgOpen Access
Meta-Learning Based Multi-Fidelity Deep Neural Networks Metamodel Method
Author(s) -
Li Zhang,
Chen Jiang-tao,
Xiong Fenfen,
Ren Chengkun,
Chao Lü,
严重影响系统性能,
通过对高精度耗时的仿真模型构 建近似模型进行响应预测,
。 为此,
产生了多可信度建模的思想,
在保证预测精度的同时,
尽可能地降低计算量
Publication year - 2022
Publication title -
journal of mechanical engineering
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 0.342
H-Index - 50
ISSN - 0577-6686
DOI - 10.3901/jme.2022.01.190
Subject(s) - metamodeling , computer science , artificial intelligence , artificial neural network , fidelity , deep learning , machine learning , deep neural networks , software engineering , telecommunications

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom