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  • The problem of optimal partitioning by minimizing pooled-within-variance of groups is addressed. Three state-of-the-art adaptive differential evolution algorithms are compared on four real-world data sets. A~novel hybrid differential evolution algorithm, including k-means algorithm for local search is proposed. The experimental comparison is done with either the plain adaptive differential evolution variants or the hybrid algorithms. Experimental results showed that hybrid algorithms are substantially better preforming when compared with plain differential evolution variants. Among hybrid variants, the competitive differential evolution appeared to be the most efficient.
  • The problem of optimal partitioning by minimizing pooled-within-variance of groups is addressed. Three state-of-the-art adaptive differential evolution algorithms are compared on four real-world data sets. A~novel hybrid differential evolution algorithm, including k-means algorithm for local search is proposed. The experimental comparison is done with either the plain adaptive differential evolution variants or the hybrid algorithms. Experimental results showed that hybrid algorithms are substantially better preforming when compared with plain differential evolution variants. Among hybrid variants, the competitive differential evolution appeared to be the most efficient. (en)
Title
  • Hybrid Adaptive Differential Evolution in Partitional Clustering
  • Hybrid Adaptive Differential Evolution in Partitional Clustering (en)
skos:prefLabel
  • Hybrid Adaptive Differential Evolution in Partitional Clustering
  • Hybrid Adaptive Differential Evolution in Partitional Clustering (en)
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  • RIV/61988987:17610/11:A12011VT!RIV12-MSM-17610___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
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  • S, Z(MSM6198898701)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...iv/duvernostUdaju
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  • 203031
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  • RIV/61988987:17610/11:A12011VT
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  • Optimal partitioning; trace-within minimizing criterion; adaptive differential evolution; k-means algorithm; hybrid search (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [009660D7E42F]
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  • Brno
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  • Brno
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  • MENDEL 2011 17th International Conference on Soft Computing
http://linked.open...in/vavai/riv/obor
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  • Tvrdík, Josef
  • Křivý, Ivan
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http://linked.open...n/vavai/riv/zamer
number of pages
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  • University of Technology
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  • 978-80-214-4302-0
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  • 17610
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