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Solution of Partial Differential Equations on Radial Basis Functions Networks

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Proceedings of International Scientific Conference on Telecommunications, Computing and Control

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 220))

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Abstract

The solution of boundary value problems described by partial differential equations on networks of radial basis functions is considered. An analysis of gradient learning algorithms for radial basis functions networks showed that the widely used first-order method, the gradient descent method, does not provide a high learning speed and solution accuracy. The fastest method of the second order, the trust region method, is very complex. A learning algorithm based on the Levenberg–Marquardt method is proposed. The proposed algorithm, with a simpler implementation, showed comparable results in comparison with the trust region method.

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Authors and Affiliations

  1. Penza State University, Penza, Russia

    Mohie Alqezweeni & Vladimir Gorbachenko

Authors
  1. Mohie Alqezweeni
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  2. Vladimir Gorbachenko
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Correspondence to Mohie Alqezweeni .

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Editors and Affiliations

  1. Higher School of Software Engineering, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia

    Nikita Voinov

  2. Department of Computer Science and Biomedical Engineering, Graz University of Technology, Graz, Austria

    Tobias Schreck

  3. School of Maths, Computer Science and Engineering, City, University of London, London, UK

    Sanowar Khan

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Alqezweeni, M., Gorbachenko, V. (2021). Solution of Partial Differential Equations on Radial Basis Functions Networks. In: Voinov, N., Schreck, T., Khan, S. (eds) Proceedings of International Scientific Conference on Telecommunications, Computing and Control. Smart Innovation, Systems and Technologies, vol 220. Springer, Singapore. https://doi.org/10.1007/978-981-33-6632-9_42

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  • DOI: https://doi.org/10.1007/978-981-33-6632-9_42

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-33-6631-2

  • Online ISBN: 978-981-33-6632-9

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