Self-adaptive Artificial Neural Network in Numerical Models Calibration

被引：0
|
作者：
Kucerova, Anna [1 ]
Mares, Tomas [1 ]
机构：
[1] Czech Tech Univ, Fac Civil Engn, Dept Mech, Prague 16629, Czech Republic
来源：
ARTIFICIAL NEURAL NETWORKS-ICANN 2010, PT I | 2010年 / 6352卷
关键词：
Artificial neural network; multi-layer perceptron; approximation; nonlinear relations; back-propagation; parameter identification;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The layered neural networks are considered as very general tools for approximation. In the presented contribution, a neural network with a very simple rule for the choice of an appropriate number of hidden neurons is applied to a material parameters' identification problem. Two identification strategies are compared. In the first one, the neural network is used to approximate the numerical model predicting the response for a given set of material parameters and loading. The second mode employs the neural network for constructing an inverse model, where material parameters are directly predicted for a given response.
引用
收藏
页码：347 / 350
页数：4
相关论文
共 50 条
  • [1] Self-Adaptive Superpixels Based on Neural Network Models
    Bai, Xiuxiu
    Wang, Cong
    Tian, Zhiqiang
    [J]. IEEE ACCESS, 2020, 8 : 137254 - 137262
  • [2] Self-adaptive deep neural network: Numerical approximation to functions and PDEs
    Cai, Zhiqiang
    Chen, Jingshuang
    Liu, Min
    [J]. JOURNAL OF COMPUTATIONAL PHYSICS, 2022, 455
  • [3] Automatic Coupler Design Based on Artificial Neural Network With Self-Adaptive Local Surrogates
    Liu, Anlan
    Leng, Maoheng
    Pan, Guangyuan
    Yu, Ming
    [J]. IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2022, 70 (11) : 4711 - 4725
  • [4] Self-Adaptive Mussels Wandering Optimization Algorithm with Application for Artificial Neural Network Training
    Abusnaina, Ahmed A.
    Abdullah, Rosni
    Kattan, Ali
    [J]. JOURNAL OF INTELLIGENT SYSTEMS, 2020, 29 (01) : 345 - 363
  • [5] Rock recognition and identification for selective mechanical mining: a self-adaptive artificial neural network approach
    Rachel Xu
    Ewan J. Sellers
    Ebrahim Fathi-Salmi
    [J]. Bulletin of Engineering Geology and the Environment, 2023, 82
  • [6] Rock recognition and identification for selective mechanical mining: a self-adaptive artificial neural network approach
    Xu, Rachel
    Sellers, Ewan J. J.
    Fathi-Salmi, Ebrahim
    [J]. BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT, 2023, 82 (07)
  • [7] Self-adaptive Artificial Intelligence
    de Lemos, Rogerio
    Grzes, Marek
    [J]. 2019 IEEE/ACM 14TH INTERNATIONAL SYMPOSIUM ON SOFTWARE ENGINEERING FOR ADAPTIVE AND SELF-MANAGING SYSTEMS (SEAMS 2019), 2019, : 155 - 156
  • [8] Camera Calibration by Hybrid Hopfield Network and Self-Adaptive Genetic Algorithm
    Xiang, Wen-jiang
    Zhou, Zhi-xiong
    Ge, Dong-yuan
    Zhang, Qing-ying
    Yao, Qing-he
    [J]. MEASUREMENT SCIENCE REVIEW, 2012, 12 (06): : 302 - 308
  • [9] The design of self-adaptive controller based on Hopfield neural network
    Xu Wen-shang
    Chen Shao-hua
    [J]. ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL I, PROCEEDINGS, 2009, : 112 - 116
  • [10] SAPNN: self-adaptive probabilistic neural network for medical diagnosis
    Xiong, Yibin
    Wu, Jun
    Wang, Qian
    Wei, Dandan
    [J]. INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING, 2024, 27 (01) : 68 - 77
12345