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Description
  • To simplify a numerical analysis of complicated real microstructures, a material representative volume element is defined. It is based on a binary (black and white) image, which statistically resembles a corresponding real microstructure. Several statistical descriptors suitable for the microstructure characterization of a random media can be considered. Then, for example a unit cell can be derived from the optimization procedure formulated in terms of selected statistical descriptors. The aim of the work described in this paper is to resolve this issue using multi-objective optimization techniques. The goal is to approximate as closely as possible the true Pareto front as a trade-off of competing objectives. The performance of the multi-objective algorithm is verified by the reconstruction of given artificial images and is compared with results of the single-objective counterparts.
  • To simplify a numerical analysis of complicated real microstructures, a material representative volume element is defined. It is based on a binary (black and white) image, which statistically resembles a corresponding real microstructure. Several statistical descriptors suitable for the microstructure characterization of a random media can be considered. Then, for example a unit cell can be derived from the optimization procedure formulated in terms of selected statistical descriptors. The aim of the work described in this paper is to resolve this issue using multi-objective optimization techniques. The goal is to approximate as closely as possible the true Pareto front as a trade-off of competing objectives. The performance of the multi-objective algorithm is verified by the reconstruction of given artificial images and is compared with results of the single-objective counterparts. (en)
Title
  • Multi-Objective Reconstruction of Random Media
  • Multi-Objective Reconstruction of Random Media (en)
skos:prefLabel
  • Multi-Objective Reconstruction of Random Media
  • Multi-Objective Reconstruction of Random Media (en)
skos:notation
  • RIV/68407700:21110/13:00206799!RIV14-MSM-21110___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GAP105/11/0411), 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
  • 90119
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21110/13:00206799
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • multi-objective optimization; genetic algorithm; non-dominated sorting genetic algorithm; two-point probability function; two-point cluster function; image reconstruction (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [88A1ADD485C1]
http://linked.open...v/mistoKonaniAkce
  • Cagliari
http://linked.open...i/riv/mistoVydani
  • Stirling
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the Third International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering
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
  • Lepš, Matěj
  • Zeman, Jan
  • Pospíšilová, Adéla
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 1759-3433
number of pages
http://purl.org/ne...btex#hasPublisher
  • Civil-Comp Press Ltd
https://schema.org/isbn
  • 978-1-905088-58-4
http://localhost/t...ganizacniJednotka
  • 21110
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