Adaptive subset searching-based deep neural network method for structural reliability analysis

2021 ◽  
pp. 107778
Author(s):  
Yuequan Bao ◽  
Zhengliang Xiang ◽  
Hui Li
Keyword(s):  
Neural Network ◽  
Reliability Analysis ◽  
Deep Neural Network ◽  
Structural Reliability ◽  
Neural Network Method ◽  
Structural Reliability Analysis ◽  
Network Method

An Effective Deep Neural Network Method for Prediction of Battery State at Cell and Module Level

2021 ◽  
pp. 2100048
Author(s):  
T. Nguyen-Thoi ◽  
Xujian Cui ◽  
Akhil Garg ◽  
Liang Gao ◽  
Tam T. Truong
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Neural Network Method ◽  
Network Method

Structural Reliability Analysis Using Fourier Orthogonal Neural Network Method

2013 ◽  
Vol 838-841 ◽  
pp. 360-363 ◽  
Author(s):  
Li Rong Sha ◽  
Yue Yang
Keyword(s):  
Neural Network ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Failure Probability ◽  
Structural Reliability ◽  
Random Variables ◽  
Structural Reliability Analysis ◽  
Surface Method ◽  
Structural Responses

In order to predict the failure probability of a complicated structure, the structural responses usually need to be predicted by a numerical procedure, such as FEM method. The response surface method could be used to reduce the computational effort required for reliability analysis. However the conventional response surface method is still time consuming when the number of random variables is large. In this paper, a Fourier orthogonal neural network (FONN)-based response surface method is proposed. In this method, the relationship between the random variables and structural responses is established using FONN models. Then the FONN model is connected to the first order and second moment method (FORM) to predict the failure probability. Numerical example result shows that the proposed approach is efficient and accurate, and is applicable to structural reliability analysis.

scholarly journals Prediction of Bioprocess Production Using Deep Neural Network Method

2017 ◽  
Vol 15 (2) ◽  
pp. 805
Author(s):  
Amirah Baharin ◽  
Afnizanfaizal Abdullah ◽  
Siti Noorain Mohmad Yousoff
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Neural Network Method ◽  
Network Method
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