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Randomized learning methods for artificial neural networks

2017/27/B/ST6/01804

Keywords

Descriptors

  • ST6_7: Sztuczna inteligencja, systemy inteligentne i wieloagentowe
  • ST6_11: Uczenie maszynowe, statystyczne przetwarzanie danych i zastosowanie w przetwarzaniu sygnałów

Panel

ST6 – Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems

Host institution

Politechnika Częstochowska, Wydział Elektryczny

Voivodeship: śląskie

Other projects carried out by the institution »

Principal investigator (from the host institution)

dr hab. Grzegorz Michał Dudek

Number of co-investigators in the project: 1

Call

OPUS 14 – announced on 2017-09-15

Amount awarded
152 400 PLN
Project start date
2018-06-29
Project end date
2021-06-28
Project duration
36 months (the same as in the proposal)
Project status
Project settled

Project description

Download the project description in a pdf file

Note — project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Equipment purchased [PL]

  1. Zestaw komputerowy (stacjonarny). Cost: 18 000 PLN

Information in the final report

Publication in academic press/journals (1)

  1. Generating random weights and biases in feedforward neural networks with random hidden nodes

    Authors:
    Grzegorz Dudek
    Academic press:
    Information Sciences (year: 2019, volume: 481, pages: 33-56), Publisher: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.ins.2018.12.063 – link to the publication

Articles in post-conference publications (10)

  1. Are Direct Links Necessary in Random Vector Functional Link Networks for Regression

    Authors:
    Grzegorz Dudek
    Conference:
    19th International Conference on Artificial Intelligence and Soft Computing (year: 2020, pages: 60-70), Publisher: Springer
    Date:
    conference 21-25 czerwca 2020
    Status:
    Published

  2. Sensitivity Analysis of the Neural Networks Randomized Learning

    Authors:
    Grzegorz Dudek
    Conference:
    18th International Conference on Artificial Intelligence and Soft Computing (year: 2019, pages: 51-61), Publisher: Springer
    Date:
    conference 16-20 czerwca 2019
    Status:
    Published
    DOI:
    link to the publication

  3. Data-Driven Randomized Learning of Feedforward Neural Networks

    Authors:
    Grzegorz Dudek
    Conference:
    International Joint Conference on Neural Networks (year: 2020, pages: 46030), Publisher: IEEE
    Date:
    conference 19-24 Lipca 2020
    Status:
    Published

  4. Generating Random Parameters in Feedforward Neural Networks with Random Hidden Nodes: Drawbacks of the Standard Method and How to Improve It

    Authors:
    Grzegorz Dudek
    Conference:
    International Conference on Neural Information Processing, ICONIP 2020 (year: 2020, pages: 598-606), Publisher: Springer
    Date:
    conference 18-22.11.2020
    Status:
    Published

  5. New Methods of Generating Random Parameters in Feedforward Neural Networks with Random Hidden Nodes

    Authors:
    Grzegorz Dudek
    Conference:
    Polskie Porozumienie na rzecz Rozwoju Sztucznej Inteligencji PP-RAI (year: 2019, pages: 269-272), Publisher: Department of Systems and Computer Networks, Faculty of Electronics Wroclaw University of Science and Technology
    Date:
    conference 16-18 października 2019
    Status:
    Published
    DOI:
    link to the publication

  6. Improving Randomized Learning of Feedforward Neural Networks by Appropriate Generation of Random Parameter

    Authors:
    Grzegorz Dudek
    Conference:
    15th International Work-Conference on Artificial Neural Networks (year: 2019, pages: 517-530), Publisher: Springer
    Date:
    conference 12-14 czerwca 2019
    Status:
    Published
    DOI:
    link to the publication

  7. Data-Driven Learning of Feedforward Neural Networks with Different Activation Functions

    Authors:
    Grzegorz Dudek
    Conference:
    20th International Conference on Artificial Intelligence and Soft Computing (year: 2021, pages: 66-77), Publisher: Springer
    Date:
    conference 2021.06.20-24
    Status:
    Published

  8. Randomized Neural Networks for Forecasting Time Series with Multiple Seasonality

    Authors:
    Grzegorz Dudek
    Conference:
    16th International Work-Conference on Artificial Neural Networks (year: 2021, pages: 196-207), Publisher: Springer
    Date:
    conference 2021.06.16-18
    Status:
    Published

  9. Autoencoder based Randomized Learning of Feedforward Neural Networks for Regression

    Authors:
    Grzegorz Dudek
    Conference:
    International Joint Conference on Neural Networks (year: 2021, pages: 196-207), Publisher: IEEEXplore
    Date:
    conference 2021.07.18-23
    Status:
    Published

  10. Ensembles of Randomized Neural Networks for Pattern-based Time Series Forecasting

    Authors:
    Grzegorz Dudek, Paweł Pełka
    Conference:
    International Conference on Neural Information Processing, ICONIP 2021 (year: 2021), Publisher: Springer
    Status:
    Accepted for publication

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Graphic design and implementation: Jakub Piotrowski