
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/">
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:rights>All rights reserved</dc:rights>
  <dc:format>application/pdf</dc:format>
  <dc:format>3707045 bytes</dc:format>
  <dc:creator>Radonja, Pero J.</dc:creator>
  <dc:source>Zbornik radova Instituta za šumarstvo</dc:source>
  <dc:source>number: 44-45</dc:source>
  <dc:source>startpage: 37</dc:source>
  <dc:source>endpage: 50</dc:source>
  <dc:language>srp</dc:language>
  <dc:publisher>Institut za šumarstvo</dc:publisher>
  <dc:title xml:lang="srp">EFIKASNI POSTUPCI IZRAVNAVANJA VISINSKE KRIVE PRIMENOM METODA VEŠTAČKE INTELIGENCIJE</dc:title>
  <dc:title xml:lang="eng">EFICIENCI PROCEDURE OF HEIGHT CURVE FITTING USING ARTIFICIAL INTELLIGENCE METHOD</dc:title>
  <dc:identifier>https://unilib.phaidrabg.rs/o:7115</dc:identifier>
  <dc:identifier>ISSN: 0351-9147</dc:identifier>
  <dc:description xml:lang="eng">In this paper application of different algorithms based on the artificial
intelligence methods in process of height curve fitting is shown. The linear
neural networks, the nonlinear back-propagation learning networks and radialbasis
function networks are considered. The efficiency of the adaptive Sugeno
fuzzy algorithm is analised also.</dc:description>
  <dc:description xml:lang="srp">U radu je prikazana primena različitih algoritama baziranih na metodama
veštačke inteligencije, kod postupka izravnavanja visinske krive. Posmatrane
su linearne neuronske mreže, zatim nelinearne mreže sa propagacijom unazad
kao i neuronske mreže sa radijalnim neuronima. Posebno je analizirana
efikasnost adaptivnog fazi algoritma Sugeno tipa.</dc:description>
  <dc:subject xml:lang="srp">vestacka inteligencija, linearne neuronske mreze, LevenbergMarqurdtov algoritam, mreze bazirane na radijalnim funkcijama, fazi sistemi, izravnavanje.</dc:subject>
  <dc:subject xml:lang="eng">artificial intelligence, linear neural networks, LevenbergMarquardt algorithm, radial-basis function networks, fuzzy systems, fitting.</dc:subject>
  <dc:date>2001</dc:date>
</oai_dc:dc>
