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Detecting potential design weaknesses in shade through network feature analysis

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63517051" target="_blank" >RIV/70883521:28140/17:63517051 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/chapter/10.1007/978-3-319-59650-1_56" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-59650-1_56</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-59650-1_56" target="_blank" >10.1007/978-3-319-59650-1_56</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Detecting potential design weaknesses in shade through network feature analysis

  • Original language description

    This preliminary study presents a hybridization of two research fields – evolutionary algorithms and complex networks. A network is created by the dynamic of an evolutionary algorithm, namely Success-History based Adaptive Differential Evolution (SHADE). Network feature, node degree centrality, is used afterward to detect potential design weaknesses of SHADE algorithm. This approach is experimentally tested on the CEC2015 benchmark set of test functions and future directions in the research are proposed.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  • ISBN

    978-3-319-59649-5

  • ISSN

    0302-9743

  • e-ISSN

    neuvedeno

  • Number of pages

    12

  • Pages from-to

    662-673

  • Publisher name

    Springer-Verlag Berlin

  • Place of publication

    Heidelberg

  • Event location

    La Rioja

  • Event date

    Jun 21, 2017

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article