About: Competitive Self-Adaptation in Evolutionary Algorithms     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • Heuristic search for the global minimum is studied. This paper is focused on the adaptation of control parameters in differential evolution (DE) and in controlled random search (CRS). The competition of different control parameter settings is used in order to ensure the self-adaptation of parameter values within the search process. In the generalized CRS the self-adaptation is ensured by several competing local-search heuristics for the generation of a new trial point. DE was experimentally compared with other adaptive algorithms on a benchmark, self-adaptive CRS was compared in estimation of regression parameters on NIST nonlinear regression datasets. The competitive algorithms outperformed other algorithms both in the reliability and in the convergence rate.
  • Heuristic search for the global minimum is studied. This paper is focused on the adaptation of control parameters in differential evolution (DE) and in controlled random search (CRS). The competition of different control parameter settings is used in order to ensure the self-adaptation of parameter values within the search process. In the generalized CRS the self-adaptation is ensured by several competing local-search heuristics for the generation of a new trial point. DE was experimentally compared with other adaptive algorithms on a benchmark, self-adaptive CRS was compared in estimation of regression parameters on NIST nonlinear regression datasets. The competitive algorithms outperformed other algorithms both in the reliability and in the convergence rate. (en)
Title
  • Competitive Self-Adaptation in Evolutionary Algorithms
  • Competitive Self-Adaptation in Evolutionary Algorithms (en)
skos:prefLabel
  • Competitive Self-Adaptation in Evolutionary Algorithms
  • Competitive Self-Adaptation in Evolutionary Algorithms (en)
skos:notation
  • RIV/61988987:17610/07:A1000KT4!RIV10-MSM-17610___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA201/05/0284), P(GA201/06/0612), Z(MSM6198898701)
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
  • 414477
http://linked.open...ai/riv/idVysledku
  • RIV/61988987:17610/07:A1000KT4
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Global optimization; Differential evolution; Controlled random search; Self-adaptation. (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [B293DA54F222]
http://linked.open...v/mistoKonaniAkce
  • Ostrava
http://linked.open...i/riv/mistoVydani
  • Ostrava
http://linked.open...i/riv/nazevZdroje
  • NEW DIMENSIONS IN FUZZY LOGIC AND RELATED TECHNOLOGIES, VOL II, PROCEEDINGS
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Tvrdík, Josef
  • Křivý, Ivan
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000264207800035
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Ostravská univerzita v Ostravě
https://schema.org/isbn
  • 978-80-7368-387-0
http://localhost/t...ganizacniJednotka
  • 17610
is http://linked.open...avai/riv/vysledek of
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software