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  • Mechatronic conceptions are most frequently characterized as synergistic conjunction of the mechanics, electrotechnics and computer science. Computer science as a platform of the realization of control algorithms especially increasingly runs the soft computing algorithms. Soft computing differs from conventional (hard) computing in the basic principle: it exploits the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The most important coomponents of soft computing are fuzzy logic, neural network theory, probabilistic reasoning, genetic algorithm, chaos theory and parts of machine learning theory. Fundamental issue is that the principal contributions of cited components are complementary, not competitive (leading on hybrid systems creation, etc.). The survey of the most interesting ideas of learning used in soft computing is introduced in this contribution.
  • Mechatronic conceptions are most frequently characterized as synergistic conjunction of the mechanics, electrotechnics and computer science. Computer science as a platform of the realization of control algorithms especially increasingly runs the soft computing algorithms. Soft computing differs from conventional (hard) computing in the basic principle: it exploits the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The most important coomponents of soft computing are fuzzy logic, neural network theory, probabilistic reasoning, genetic algorithm, chaos theory and parts of machine learning theory. Fundamental issue is that the principal contributions of cited components are complementary, not competitive (leading on hybrid systems creation, etc.). The survey of the most interesting ideas of learning used in soft computing is introduced in this contribution. (en)
Title
  • Learning in Mechatronic Conceptions
  • Learning in Mechatronic Conceptions (en)
skos:prefLabel
  • Learning in Mechatronic Conceptions
  • Learning in Mechatronic Conceptions (en)
skos:notation
  • RIV/00216305:26210/01:PU22770!RIV/2002/GA0/262102/N
http://linked.open.../vavai/riv/strany
  • 431-442
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA101/00/1471)
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  • 6
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 685145
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26210/01:PU22770
http://linked.open...riv/jazykVysledku
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  • Q-learning, computer science, control algorithms (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • CZ - Česká republika
http://linked.open...ontrolniKodProRIV
  • [96788770C93A]
http://linked.open...i/riv/nazevZdroje
  • Inženýrská mechanika - Engineering Mechanics
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...ocetUcastnikuAkce
http://linked.open...nichUcastnikuAkce
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 8
http://linked.open...iv/tvurceVysledku
  • Březina, Tomáš
issn
  • 1210-2717
number of pages
http://localhost/t...ganizacniJednotka
  • 26210
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