Recurrent neural network (RNN) and long short-term memory neural network (LSTM) based data-driven methods for identifying cohesive zone law parameters of nickel-modified carbon nanotube reinforced sintered nano-silver adhesives-Reference-Cited by-同舟云学术

Recurrent neural network (RNN) and long short-term memory neural network (LSTM) based data-driven methods for identifying cohesive zone law parameters of nickel-modified carbon nanotube reinforced sintered nano-silver adhesives

Published:2024-06 Issue: Volume:39 Page:108991
ISSN:2352-4928
Container-title:Materials Today Communications
language:en
Short-container-title:Materials Today Communications

Author:

Dai Yanwei,Wei Jiahui,Qin Fei

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

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