Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

Keywords

Equipment

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A new approach for effective training of complex inteligent systems

2015/17/B/ST6/01880

Keywords:

Learning Systems Neural Networks Learning Algorithms ELM – Extreme Learning Machines SVM – Support Vector Machine

Descriptors:

  • ST6_7: Artificial intelligence, intelligent systems, multi-agent systems

Panel:

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

Host institution :

Wyższa Szkoła Informatyki i Zarządzania w Rzeszowie, Wydział Informatyki Stosowanej

woj. podkarpackie

Other projects carried out by the institution 

Principal investigator (from the host institution):

prof. Bogdan Wilamowski 

Number of co-investigators in the project: 6

Call: OPUS 9 - announced on 2015-03-16

Amount awarded: 621 200 PLN

Project start date (Y-m-d): 2016-01-26

Project end date (Y-m-d): 2019-07-25

Project duration:: 42 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. Monitor LCD (3 600 PLN)
  2. Komputer stacjonarny (17 000 PLN)
  3. Oprogramowanie specjalistyczne (15 000 PLN)

Information in the final report

  • Publication in academic press/journals (4)
  • Articles in post-conference publications (7)
  • Book publications / chapters in book publications (5)
  1. Neural Network Training With Levenberg–Marquardt and Adaptable Weight Compression
    Authors:
    James S. Smith, Bo Wu, Bogdan M. Wilamowski
    Academic press:
    IEEE Transactions on Neural Networks and Learning Systems (rok: 2018, tom: Vol: 30 , Is: 2, strony: 580 - 587), Wydawca: IEEE
    Status:
    Published
    DOI:
    10.1109/TNNLS.2018.2846775 - link to the publication
  2. Efficient training of RBF Neural Networks
    Authors:
    Paweł Różycki, Janusz Kolbusz, Tomasz Bartczak
    Academic press:
    Kwartalnik Naukowy Uczelni Vistula (rok: 2018, tom: 2(56), strony: 257-268), Wydawca: Akademia Finansów i Biznesu Vistula
    Status:
    Published
    DOI:
    brak - link to the publication
  3. Nonlinear System Modeling using RBF networks for industrial application
    Authors:
    Xi Meng; Pawel Rozycki; Jun-Fei Qiao; Bogdan M. Wilamowski
    Academic press:
    IEEE Transactions on Industrial Informatics (rok: 2018, tom: VOL. 14, NO. 3, strony: 931-940), Wydawca: IEEE Transactions on Industrial Informatics
    Status:
    Published
    DOI:
    10,1109 - link to the publication
  4. The Study of the Influence of Architecture on Effectiveness of Deep Neural Networks Training
    Authors:
    Janusz Kolbusz, Paweł Różycki, Tomasz Bartczak
    Academic press:
    Zeszyty Naukowe Uczelni Vistula (rok: 2018, tom: 59(2), strony: 60-71), Wydawca: Akademia Finansów i Biznesu Vistula
    Status:
    Published
    DOI:
    brak - link to the publication
  1. Big Data and Deep Learning
    Authors:
    B. M. Wilamowski, Bo Wu, Janusz Korniak
    Conference:
    IEEE 20th International Conference on Intelligent Engineering Systems (INES'16) (rok: 2016, ), Wydawca: IEEE
    Data:
    konferencja 30-2 June 2016
    Status:
    Published
  2. Effective Training of RBF Networks
    Authors:
    P. Rozycki, J. Kolbusz, A. Malinowski, B.M. Wilamowski
    Conference:
    12th IEEE International Conference on Human System Interaction (rok: 2019, ), Wydawca: IEEE
    Data:
    konferencja June 25-27
    Status:
    Published
  3. Estimation of Deep Neural Networks Capabilities Based on a Trigonometric Approach
    Authors:
    Paweł Różycki, Janusz Kolbusz, Bogdan Wilamowski
    Conference:
    IEEE 20th International Conference on Intelligent Engineering Systems (INES'16) (rok: 2016, ), Wydawca: IEEE
    Data:
    konferencja 30-2 June 2016
    Status:
    Published
  4. Error Back Propagation Algorithm with Adaptive Learning Rate
    Authors:
    J. Kolbusz, P. Rozycki, O. Lysenko, B. M. Wilamowski
    Conference:
    International Conference on Information and Digital Technologies (rok: 2019, ), Wydawca: IEEE
    Data:
    konferencja June 25 - 27
    Status:
    Published
  5. The Impact of Architecture on the Deep Neural Networks Training
    Authors:
    P. Rozycki, J. Kolbusz, A. Malinowski, B.M. Wilamowski
    Conference:
    12th IEEE International Conference on Human System Interaction (rok: 2019, ), Wydawca: IEEE
    Data:
    konferencja June 25-27
    Status:
    Published
  6. Approximation-based Estimation of Learning Rate for Error Back Propagation Algorithm
    Authors:
    P. Rozycki, J. Kolbusz, G. Krzos, B.M. Wilamowski
    Conference:
    23rd IEEE International Conference on Intelligent Engineering Systems (INES'19) (rok: 2019, ), Wydawca: IEEE
    Data:
    konferencja April 25-27
    Status:
    Published
  7. Implementation of Deep Neural Networks for Industry Applications
    Authors:
    P.Rozycki, J. Kolbusz, G. Krzos, B.M. Wilamowski
    Conference:
    IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society (rok: 2018, ), Wydawca: IEEE
    Data:
    konferencja 21-23 Oct. 2018
    Status:
    Published
  1. Discrete Cosine Transform Spectral Pooling Layers for Convolutional Neural Networks
    Authors:
    James S. Smith, Bogdan M. Wilamowski
    Book:
    Artificial Intelligence and Soft Computing. ICAISC 2018. Lecture Notes in Computer Science (rok: 2018, tom: vol 10841, strony: 235-246), Wydawca: Springer
    Status:
    Published
  2. Discrete Cosine Transformation as alternative to other methods of computational intelligence for function approximation
    Authors:
    Andzelika Olejczak, Janusz Korniak, B. M. Wilamowski
    Book:
    Artificial Intelligence and Soft Computing. 16th International Conference, ICAISC 2017, Zakopane, Poland, June 11-15, 2017, Proceedings, Part I (rok: 2017, tom: 1, strony: 143-153), Wydawca: Springer International Publishing AG
    Status:
    Published
  3. Constructive Cascade Learning Algorithm for Fully Connected Networks
    Authors:
    Xing Wu, Bogdan M. Wilamowski, Pawel Rozycki, Janusz Kolbusz
    Book:
    Artificial Intelligence and Soft Computing. ICAISC 2019. (rok: 2019, tom: I, strony: 236-247), Wydawca: Springer
    Status:
    Published
  4. Soft Patterns Reduction for RBF network performance improvement
    Authors:
    P. Rozycki, J. Kolbusz, O. Lysenko, B.M. Wilamowski
    Book:
    Artificial Intelligence and Soft Computing. ICAISC 2018. Lecture Notes in Artificial Intelligence. (rok: 2018, tom: volume 10841, strony: 190-200), Wydawca: Springer
    Status:
    Published
  5. Neural Networks Saturation Reduction
    Authors:
    J. Kolbusz, P. Rozycki, O. Lysenko, B. M. Wilamowski
    Book:
    Artificial Intelligence and Soft Computing. ICAISC 2018. Lecture Notes in Artificial Intelligence. (rok: 2018, tom: volume 10841, strony: 108-117), Wydawca: Springer
    Status:
    Published

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