Backpropagation and Levenberg-Marquardt Algorithm for Training Finite Element Neural Network

被引：62
|
作者：
Reynaldi, Arnold [1 ]
Lukas, Samuel [2 ]
Margaretha, Helena [1 ]
机构：
[1] Pelita Harapan Univ, Fac Sci & Math, Tangerang, Banten, Indonesia
[2] Pelita Harapan Univ, Fac Comp Sci, Tangerang, Banten, Indonesia
来源：
2012 SIXTH UKSIM/AMSS EUROPEAN SYMPOSIUM ON COMPUTER MODELLING AND SIMULATION (EMS) | 2012年
关键词：
finite element method; artificial neural network; backpropagation algorithm; Levenberg-Marquardt algorithm; inverse differential problem;
D O I：
10.1109/EMS.2012.56
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, finite element based neural network is developed. The purpose is to solve differential equation and inverse problem of differential equation. Inverse problem of differential equation is a problem to solve for parameters of differential equation, assuming that the solution of the differential equation is already known beforehand. Inverse problem mainly used to approximate physical parameters of material. Finite element method will be combined with artificial neural network using backpropagation algorithm to solve differential equation and Levenberg-Marquardt training algorithm to solve inverse differential problem. By using proposed method, invers matrix calculation will not be needed for solving both differential equation and inverse differential problem. From any given differential equation, the solution will be solved first. And the solution is used to validate the parameter in differential equation, namely to solve inverse problem of that differential equation.
引用
收藏
页码：89 / 94
页数：6
相关论文
共 50 条
  • [41] Neural network predictive control for dissolved oxygen based on levenberg-marquardt algorithm
    Li M.
    Zhou L.
    Wang J.
    Nongye Jixie Xuebao, 6 (297-302): : 297 - 302
  • [42] Design of Neural Network With Levenberg-Marquardt and Bayesian Regularization Backpropagation for Solving Pantograph Delay Differential Equations
    Khan, Imtiaz
    Raja, Muhammad Asif Zahoor
    Shoaib, Muhammad
    Kumam, Poom
    Alrabaiah, Hussam
    Shah, Zahir
    Islam, Saeed
    IEEE ACCESS, 2020, 8 : 137918 - 137933
  • [43] An echo state network based on Levenberg-Marquardt algorithm
    Wang, Lei
    Yang, Cuili
    Qiao, Junfei
    Wang, Gongming
    PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 3899 - 3904
  • [44] Levenberg-Marquardt backpropagation algorithm for parameter identification of solid oxide fuel cells
    Yang, Bo
    Chen, Yijun
    Guo, Zhengxun
    Wang, Jingbo
    Zeng, Chunyuan
    Li, Danyang
    Shu, Hongchun
    Shan, Jieshan
    Fu, Ting
    Zhang, Xiaoshun
    INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2021, 45 (12) : 17903 - 17923
  • [45] Application of the Levenberg-Marquardt method to the training of spiking neural networks
    Silva, Sergio M.
    Ruano, Antonio E.
    2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10, 2006, : 3978 - +
  • [46] On-line training of neural networks: A sliding window approach for the Levenberg-Marquardt algorithm
    Dias, FM
    Antunes, A
    Vieira, J
    Mota, AM
    ARTIFICIAL INTELLIGENCE AND KNOWLEDGE ENGINEERING APPLICATIONS: A BIOINSPIRED APPROACH, PT 2, PROCEEDINGS, 2005, 3562 : 577 - 585
  • [47] Application of Levenberg-Marquardt method to the training of spiking neural networks
    Silva, SM
    Ruano, AE
    PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND BRAIN, VOLS 1-3, 2005, : 1354 - 1358
  • [48] Recursive Bayesian Levenberg-Marquardt training of recurrent neural networks
    Mirikitani, Derrick
    Nikolaev, Nikolay
    2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6, 2007, : 282 - 287
  • [49] MONITORING OF PM2.5 POLLUTANT INDEX IN THE AIR BASED ON THE GENETIC ALGORITHM- LEVENBERG-MARQUARDT ALGORITHM-BACKPROPAGATION NEURAL NETWORK
    Zhang, Yong
    Cao, Guoliang
    Lie, Pinpin
    FRESENIUS ENVIRONMENTAL BULLETIN, 2019, 28 (11A): : 8721 - 8728
  • [50] Optimisation Using Levenberg-Marquardt Algorithm of Neural Networks for Iris
    Sayed, Asim
    Sardeshmukh, M.
    Limkar, Suresh
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON FRONTIERS OF INTELLIGENT COMPUTING: THEORY AND APPLICATIONS (FICTA) 2013, 2014, 247 : 91 - 98
12345