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A Novel Methods Based on Clustering Algorithms as The Neural Network Preprocessing

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43955832" target="_blank" >RIV/49777513:23520/19:43955832 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/SAMI.2019.8782767" target="_blank" >http://dx.doi.org/10.1109/SAMI.2019.8782767</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/SAMI.2019.8782767" target="_blank" >10.1109/SAMI.2019.8782767</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Novel Methods Based on Clustering Algorithms as The Neural Network Preprocessing

  • Original language description

    This paper presents experiments in the preprocessing area for Radial Basic Function Neural Network (RBF NN). The main ideas of it are to find optimal preprocessing methods and algorithms, which can optimize input parameters and expedite the processing of neural network. The proposed methods are some novel experiments with flexible shape parameters and automated determination of the neural network initial parameters

  • 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

    2019

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    SAMI 2019 • IEEE 17th World Symposium on Applied Machine Intelligence and Informatics

  • ISBN

    978-1-72810-250-4

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    317-322

  • Publisher name

    IEEE

  • Place of publication

    Herlany

  • Event location

    Herlany

  • Event date

    Jan 24, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000502817400054