Study on the development of complex network for evolutionary and swarm based algorithms

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63517313" target="_blank" >RIV/70883521:28140/17:63517313 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27240/17:10238535 RIV/61989100:27740/17:10238535

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-62428-0_12" target="_blank" >http://dx.doi.org/10.1007/978-3-319-62428-0_12</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-62428-0_12" target="_blank" >10.1007/978-3-319-62428-0_12</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Study on the development of complex network for evolutionary and swarm based algorithms

Popis výsledku v původním jazyce

This contribution deals with the hybridization of complex network frameworks and metaheuristic algorithms. The population is visualized as an evolving complex network that exhibits non-trivial features. It briefly investigates the time and structure development of a complex network within a run of selected metaheuristic algorithms – i.e. PSO and Differential Evolution (DE). Two different approaches for the construction of complex networks are presented herein. It also briefly discusses the possible utilization of complex network attributes. These attributes include an adjacency graph that depicts interconnectivity, while centralities provide an overview of convergence and stagnation, and clustering encapsulates the diversity of the population, whereas other attributes show the efficiency of the network. The experiments were performed for one selected DE/PSO strategy and one simple test function.

Název v anglickém jazyce

Study on the development of complex network for evolutionary and swarm based algorithms

Popis výsledku anglicky

This contribution deals with the hybridization of complex network frameworks and metaheuristic algorithms. The population is visualized as an evolving complex network that exhibits non-trivial features. It briefly investigates the time and structure development of a complex network within a run of selected metaheuristic algorithms – i.e. PSO and Differential Evolution (DE). Two different approaches for the construction of complex networks are presented herein. It also briefly discusses the possible utilization of complex network attributes. These attributes include an adjacency graph that depicts interconnectivity, while centralities provide an overview of convergence and stagnation, and clustering encapsulates the diversity of the population, whereas other attributes show the efficiency of the network. The experiments were performed for one selected DE/PSO strategy and one simple test function.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

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

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

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

ISBN

978-3-319-62427-3

ISSN

0302-9743

e-ISSN

neuvedeno

Počet stran výsledku

11

Strana od-do

151-161

Název nakladatele

Springer Verlag

Místo vydání

Berlín

Místo konání akce

Cancun

Datum konání akce

23. 10. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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