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Description
  • The article introduces a hybrid intelligent system for point localization in 3D Euclidean space. There are two models presented. The first one is based on neural networks and the second one represents a classical approach. The classical model calculates Euclidean distances between two points in the defined domain. As regards the experimental study, we proposed appropriate topologies of the systems that depend on the required accuracy. At first, we identified distances between a randomly generated point and a reference points in the defined domain. Then a neural network uses the obtained distances as its inputs to determine the actual position of the point in the domain space. The experimental study was repeated several times. All obtained results are mutually compared in the conclusion.
  • The article introduces a hybrid intelligent system for point localization in 3D Euclidean space. There are two models presented. The first one is based on neural networks and the second one represents a classical approach. The classical model calculates Euclidean distances between two points in the defined domain. As regards the experimental study, we proposed appropriate topologies of the systems that depend on the required accuracy. At first, we identified distances between a randomly generated point and a reference points in the defined domain. Then a neural network uses the obtained distances as its inputs to determine the actual position of the point in the domain space. The experimental study was repeated several times. All obtained results are mutually compared in the conclusion. (en)
Title
  • Hybrid Intelligent System for Point Localization
  • Hybrid Intelligent System for Point Localization (en)
skos:prefLabel
  • Hybrid Intelligent System for Point Localization
  • Hybrid Intelligent System for Point Localization (en)
skos:notation
  • RIV/61988987:17310/14:A1501B2G!RIV15-MSM-17310___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 20038
http://linked.open...ai/riv/idVysledku
  • RIV/61988987:17310/14:A1501B2G
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Hybrid intelligent system; Neural networks; Point localization (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D62514E041D8]
http://linked.open...v/mistoKonaniAkce
  • UTB Zlín
http://linked.open...i/riv/mistoVydani
  • Switzerland
http://linked.open...i/riv/nazevZdroje
  • Modern Trends and Techniques in Computer Science, AISC 285
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Kolcun, Alexej
  • Volná, Eva
  • Jarušek, Robert
  • Kotyrba, Martin
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 2194-5357
number of pages
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-3-319-06739-1
http://localhost/t...ganizacniJednotka
  • 17310
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