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  • The subject of investigation is to rationalize geometry from an unorganized point cloud by using artificial learning neural network. Furthermore, the focus is oriented upon aspects of efficient construction of generated topology. Neural network is connected with constrained properties, which adjust the members of the topology into predefined number of sizes while minimizing the error of deviation from the original form.
  • The subject of investigation is to rationalize geometry from an unorganized point cloud by using artificial learning neural network. Furthermore, the focus is oriented upon aspects of efficient construction of generated topology. Neural network is connected with constrained properties, which adjust the members of the topology into predefined number of sizes while minimizing the error of deviation from the original form. (en)
Title
  • Cognitive algorithms in structural optimization
  • Cognitive algorithms in structural optimization (en)
skos:prefLabel
  • Cognitive algorithms in structural optimization
  • Cognitive algorithms in structural optimization (en)
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  • RIV/68407700:21450/10:00177037!RIV11-MSM-21450___
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  • 251112
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  • RIV/68407700:21450/10:00177037
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  • Parametric design, Artificial neural network, unorganized point cloud, space frame (en)
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  • [A79B8D30D21C]
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  • Kaftan, Martin
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number of pages
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  • České vysoké učení technické v Praze
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  • 978-80-247-3624-2
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  • 21450
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