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  • Není k dispozici (cs)
  • This paper presents new application of Particle Swarm Optimization (PSO) algorithm for training Hidden Markov Models (HMMs). The problem of finding an optimal set of model parameters is numerical optimization problem constrained by stochastic character of HMM parameters. Constraint handling is carried out using three different ways and the results are compared to Baum-Welch algorithm (BW), commonly used for HMM training. The global searching PSO method is much less sensitive to local extremes and finds better solutions than the local BW algorithm, which often converges to local optima. The advantage of PSO approach was markedly evident, when longer training sequence was used.
  • This paper presents new application of Particle Swarm Optimization (PSO) algorithm for training Hidden Markov Models (HMMs). The problem of finding an optimal set of model parameters is numerical optimization problem constrained by stochastic character of HMM parameters. Constraint handling is carried out using three different ways and the results are compared to Baum-Welch algorithm (BW), commonly used for HMM training. The global searching PSO method is much less sensitive to local extremes and finds better solutions than the local BW algorithm, which often converges to local optima. The advantage of PSO approach was markedly evident, when longer training sequence was used. (en)
Title
  • Constraints in Particle Swarm Optimization of Hidden Markov Models
  • Není k dispozici (cs)
  • Constraints in Particle Swarm Optimization of Hidden Markov Models (en)
skos:prefLabel
  • Constraints in Particle Swarm Optimization of Hidden Markov Models
  • Není k dispozici (cs)
  • Constraints in Particle Swarm Optimization of Hidden Markov Models (en)
skos:notation
  • RIV/68407700:21230/06:03120667!RIV07-MSM-21230___
http://linked.open.../vavai/riv/strany
  • 1399 ; 1406
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S, Z(MSM6840770012)
http://linked.open...vai/riv/dodaniDat
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  • 469647
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/06:03120667
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Optimization; Particle Swarm Optimization; constrained; evolutionary computing; hidden Markov models (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [B53727CB82E0]
http://linked.open...v/mistoKonaniAkce
  • Burgos
http://linked.open...i/riv/mistoVydani
  • Berlin
http://linked.open...i/riv/nazevZdroje
  • Intelligent Data Engineering and Automated Learning - Proceedings of IDEAL 2006
http://linked.open...in/vavai/riv/obor
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http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
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  • Lhotská, Lenka
  • Novák, Daniel
  • Macaš, Martin
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • Springer-Verlag
https://schema.org/isbn
  • 3-540-45485-3
http://localhost/t...ganizacniJednotka
  • 21230
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