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Differential Evolution Algorithms Used to Optimize Weights of Neural Network Solving Pole-Balancing Problem

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AETA 2018 - Recent Advances in Electrical Engineering and Related Sciences: Theory and Application (AETA 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 554))

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Abstract

Differential evolution (DE) has been successfully used to solve difficult optimization problems. Every year, novel DE algorithms are developed to outperform the previous versions. The JADE is a famous DE algorithm using a mutation strategy current-to-pbest and the adaptation of control parameters. The SHADE has been developed to eliminate some bottlenecks of the JADE, especially its tendency to a premature convergence. The performance of these algorithms has been demonstrated on various benchmarks. The goal of this work is to compare the performance of the selected DE algorithms which are used to optimize the weights of the artificial neural network solving the pole-balancing problem.

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Acknowledgement

The following grants are acknowledged for the financial support provided for this research by Grant of SGS No. 2018/177, VSB - Technical University of Ostrava and under the support of NAVY and MERLIN research lab.

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Authors and Affiliations

  1. Faculty of Electrical Engineering and Computer Science, VSB – Technical University of Ostrava, 70800, Ostrava, Czech Republic

    Jan Vargovsky & Lenka Skanderova

Authors
  1. Jan Vargovsky
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  2. Lenka Skanderova
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Corresponding author

Correspondence to Jan Vargovsky .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Faculty of Electrical Engineering, VŠB-TUO, Ostrava-Poruba, Czech Republic

    Ivan Zelinka

  2. Department of Electronics, Faculty of Electrical Engineering, VŠB-TUO, Ostrava, Czech Republic

    Pavel Brandstetter

  3. International Cooperation, Research and Training Institute, Ton Duc Thang University, Ho Chi Minh, Vietnam

    Tran Trong Dao

  4. Department of Automatic Control, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Vo Hoang Duy

  5. Department of Mechanical Design Engineering, Pukyong National University, Busan, Korea (Republic of)

    Sang Bong Kim

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Vargovsky, J., Skanderova, L. (2020). Differential Evolution Algorithms Used to Optimize Weights of Neural Network Solving Pole-Balancing Problem. In: Zelinka, I., Brandstetter, P., Trong Dao, T., Hoang Duy, V., Kim, S. (eds) AETA 2018 - Recent Advances in Electrical Engineering and Related Sciences: Theory and Application. AETA 2018. Lecture Notes in Electrical Engineering, vol 554. Springer, Cham. https://doi.org/10.1007/978-3-030-14907-9_22

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  • DOI: https://doi.org/10.1007/978-3-030-14907-9_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14906-2

  • Online ISBN: 978-3-030-14907-9

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