ACCELERATED TRAINING OF CONSTITUTIVE RELATIONS FOR HISTORY-DEPENDENT COMPOSITE MATERIALS USING RECURRENT NEURAL NETWORK WITH TRANSFER LEARNING
Master's
Saved in:
Main Author: | ZHANG CHEN |
---|---|
Other Authors: | CIVIL & ENVIRONMENTAL ENGINEERING |
Format: | Theses and Dissertations |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://scholarbank.nus.edu.sg/handle/10635/236775 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | National University of Singapore |
Language: | English |
Similar Items
-
MACHINE LEARNING FOR CONSTITUTIVE MODELLING
by: DENG HAOXIANG
Published: (2022) -
Training issues and learning algorithms for feedforward and recurrent neural networks
by: TEOH EU JIN
Published: (2010) -
Building energy consumption raw data forecasting using data cleaning and deep recurrent neural networks
by: Yang, J., et al.
Published: (2022) -
Robust learning and control of time-delay nonlinear systems with deep recurrent Koopman operators
by: Han, Minghao, et al.
Published: (2024) -
An intelligent system for taxi service : analysis, prediction and visualization
by: Lu, Yu, et al.
Published: (2019)