Application of a Hopfield type neural network to the analysis of elastic problems with unilateral constraints

Authors

  • Zenon Waszczyszyn Cracow University of Technology
    Poland
  • Ewa Pabisek Cracow University of Technology
    Poland

Abstract

On the base of Hopfield- Tank neural network the Panagiotopoulos approach is briefly discussed. The approach is associated with the analysis of quadratic programming problem with unilateral constraints. Then modifications of this approach are proposed. The original Panagiotopoulos approach is illustrated by the analysis of crack detachment in an elastic body [11]. Efficiency of the proposed modifications is shown on a numerical example of an angular plate. Finally some special conclusions are expressed.

References

[1] A.V. Avdelas et.al. Neural networks for computing in the elastoplastic analysis of structures. Meccanica, 30: 1-15, 1995.
[2] G. Engeln-Müllges, F. Uhlig. Numerical Algorithms with C, Springer, Berlin- Heidelberg, 1996.
[3] L. Fausett. Fundamentals of Neural Networks - Architectures, Algorithms and Applications. Prentice Hall, Englewood Cliffs, NJ, 1994.
[4] S. Haykin. Neural Networks - A Comprehensive Foundation. Macmillan College Publ. Co., New York, 1994.
[5] J.J. Hopfield, D.W. Tank. Neural computation of decisions in optimization problems. Biological Cybernetics, 52: 141- 152, 1985.

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Published

2023-03-30

Issue

Vol. 7 No. 4 (2000)
pp. 757-765

Section

Articles

License

Copyright © The Author(s).

This work is licensed under the Creative Commons Attribution 4.0 International CC BY 4.0.

How to Cite

Waszczyszyn, Z., & Pabisek, E. (2023). Application of a Hopfield type neural network to the analysis of elastic problems with unilateral constraints. Computer Assisted Methods in Engineering and Science, 7(4), 757-765. https://cames3.ippt.pan.pl/index.php/cames/article/view/1228