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Fast Computational Approach to the Levenberg-Marquardt Algorithm for Training Feedforward Neural Networks Cover

Fast Computational Approach to the Levenberg-Marquardt Algorithm for Training Feedforward Neural Networks

Journal of Artificial Intelligence and Soft Computing Research
Volume 13 (2023): Issue 2 (March 2023)
By: Jarosław Bilski,  Jacek Smoląg,  Bartosz Kowalczyk,  Konrad Grzanek and  Ivan Izonin  
Open Access
|Mar 2023

Authors

Jarosław Bilski

jaroslaw.bilski@pcz.pl

Department of Computational Intelligence, Częstochowa University of Technology, Częstochowa, Poland

Jacek Smoląg

Department of Computational Intelligence, Częstochowa University of Technology, Częstochowa, Poland

Bartosz Kowalczyk

Department of Computational Intelligence, Częstochowa University of Technology, Częstochowa, Poland

Konrad Grzanek

Institute of Information Technologies, University of Social Sciences, Łódź, Poland

Ivan Izonin

Department of Artificial Intelligence, Lviv Polytechnic National University, Lviv, Ukraine
DOI: https://doi.org/10.2478/jaiscr-2023-0006
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Language: English
Page range: 45 - 61
Submitted on: Oct 19, 2022
Accepted on: Feb 15, 2023
Published on: Mar 11, 2023
Published by: SAN University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
feed-forward neural network,
neural network learning algorithm,
Levenberg-Marquardt algorithm,
QR decomposition,
Givens rotation
Related subjects:
Computer sciences,
Databases and data mining,
Artificial intelligence

© 2023 Jarosław Bilski, Jacek Smoląg, Bartosz Kowalczyk, Konrad Grzanek, Ivan Izonin, published by SAN University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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