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A novel approach of the approximation by patterns using hybrid RBF NN with flexible parameters

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43952470" target="_blank" >RIV/49777513:23520/18:43952470 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-030-00211-4_21" target="_blank" >http://dx.doi.org/10.1007/978-3-030-00211-4_21</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-00211-4_21" target="_blank" >10.1007/978-3-030-00211-4_21</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A novel approach of the approximation by patterns using hybrid RBF NN with flexible parameters

  • Original language description

    This paper describes a new solution to the optimization task of approximation by radial-basis-function (RBF) neural network. The proposed method is addressed to the problem of variable shape parameters for data using the RBF. It involves the max-min algorithm, the RBF neural network, the algorithm for placing new neuron’s centers and the structure of the future deep learning complex neural network (NN).

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GA17-05534S" target="_blank" >GA17-05534S: Meshless methods for large scattered spatio-temporal vector data visualization</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Computational and Statistical Methods in Intelligent Systems

  • ISBN

    978-3-030-00210-7

  • ISSN

    2194-5357

  • e-ISSN

    2194-5365

  • Number of pages

    11

  • Pages from-to

    225-235

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Szczecin

  • Event date

    Sep 12, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article