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dc.contributor.authorMašek, Jan
dc.contributor.authorVořechovský, Miroslav
dc.date.accessioned2017-12-19T07:58:14Z
dc.date.available2017-12-19T07:58:14Z
dc.date.issued2017
dc.identifier.citationSborník vědeckých prací Vysoké školy báňské - Technické univerzity Ostrava. Řada stavební. 2017, roč. 17, č. 1, s. 137-146 : il.cs
dc.identifier.urihttp://hdl.handle.net/10084/122562
dc.description.abstractThe presented paper investigates the effect of the formulation of the energy potential of a dynamical particle system used for the optimization of statistical point sampling. The dynamical particle system, originally developed as a physical analogy to the Audze-Eglajs (AE) optimization criterion and its periodical modification (PAE), effectively demonstrated that the originally proposed energy potential performs well only in poorly applicable scenarios featuring low-dimensional design domains filled with a rather high number of design points. A remedy is presented which involves a refined formulation of the energy potential, as well as its derivation. The reasoning behind this approach is also dealt with in detail.cs
dc.format.extent494657 bytes
dc.format.mimetypeapplication/pdf
dc.languageNeuvedenocs
dc.language.isoencs
dc.publisherVysoká škola báňská - Technická univerzita Ostrava
dc.relation.ispartofseriesSborník vědeckých prací Vysoké školy báňské - Technické univerzity Ostrava. Řada stavební
dc.relation.urihttps://www.degruyter.com/downloadpdf/j/tvsb.2017.17.issue-1/tvsb-2017-0016/tvsb-2017-0016.pdf
dc.rights© Vysoká škola báňská - Technická univerzita Ostrava
dc.rights© 2017 Jan Mašek et al., published by De Gruyter Open. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0
dc.subjectparticle dynamical systemcs
dc.subjectstatistical sampling optimizationcs
dc.subjectperiodic spacecs
dc.subjectparticle interaction lawscs
dc.subjectshort- and long-range interactionscs
dc.subjectself-similar designscs
dc.titleOn the influence of the interaction laws of a dynamical particle system for sample optimizationcs
dc.typearticlecs
dc.identifier.doi10.1515/tvsb-2017-0016
dc.rights.accessopenAccess


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