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	    <datestamp>2023-06-23T11:23:20Z</datestamp>
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<dc:title xml:lang="pl"><![CDATA[Rozkłady a-stabilne w ewolucyjnych algorytmachglobalnej optymalizacji parametrycznej]]></dc:title>
<dc:creator><![CDATA[Prętki, Przemysław]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[optymalizacja globalna]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[rozkłady stabilne]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[systemy wykrywania uszkodzeń]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[algorytmy ewolucyjne, systemy wykrywania uszkodzeń]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[The aim of this dissertation is to give an account on theroetical aspects of stabIe distributions and their practical application to modem stochastic global optimization algorithms. Particular emphasis is placed on special charateristics of stable family which have an effect on effectiveness of evolutionary algorithms. The c1ass of stable distributions is unique, esspeccialy against commonly used Gaussian model, from many reasons, e.g.: generally they variance is infmite while an expectation value exists only for some particular cases. In the light of these distinctive features the so-called sourounding and symmetry effect is discussed in more detail. 80th mentioned phenomena are to a large extend responsable for dec1ine in effectivness global optimization procedures that are based on Gaussian mutation.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[Results reported in the thesis show that evolutionary algorithm govemed by stable law converges to aglobal solution faster, is more roubust and retums more accurate estimates. Therefore, that c1ass of stable distributions is a perfect candidate for setting a profitabIe compromise between two opposings features: exploration of the space of candidate solutions and its exploatation. Moreover in the doctoral thesis a significant amount of attention is paid to the problem of designing the nonlinear and robust observers for discrete time dynamic systems.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[The proposed optimization methods are also successfully applied to the estimation of confidence intervals for nonlinear regression models. The approach makes it possible to avoid the most popular linearization method, so that computed adaptive bounds for nonlinear modeIs are more accurate and reliable.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[promotor: dr hab.; inż.; Andrzej Obuchowicz, Uniwersytet Zielonogórski]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[recenzenci: Prof. dr hab. inż., prof. UZ Dariusz Uciński, Uniwersytet Zielonogórski, Dr hab. inż. Jarosław Arabas, Uniwersytet Warszawski, InstytutSystemów Elektronicznych]]></dc:description>
<dc:date><![CDATA[2008]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[rozprawa doktorska]]></dc:type>
<dc:format xml:lang="pl"><![CDATA[text/html]]></dc:format>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/14669/HTML/PPretki_doktorat.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/16720/edition/14669/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:14669]]></dc:identifier>
<dc:language><![CDATA[pol]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:16720]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
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