Algoritem določanja funkcijske odvisnosti povezav med vozlišči v kompleksnih mrežah

Jesenko, David

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Title:	Algoritem določanja funkcijske odvisnosti povezav med vozlišči v kompleksnih mrežah
Authors:	ID Jesenko, David (Author) ID Žalik, Borut (Mentor) More about this mentor...
Files:	DOK_Jesenko_David_2018.pdf (11,91 MB) MD5: 2CC44B012F0A003D87B550100EDD6025 PID: 20.500.12556/dkum/76ad59af-0849-433b-9b7e-d7ab56146743
Language:	Slovenian
Work type:	Dissertation
Typology:	2.08 - Doctoral Dissertation
Organization:	FERI - Faculty of Electrical Engineering and Computer Science
Abstract:	V doktorski disertaciji predstavimo nov dvonivojski evolucijski algoritem za določanje funkcijske odvisnosti med netopološkimi lastnostmi vozlišč in povezavami v kompleksnih mrežah. Rezultat algoritma je neenačba, ki določa povezljivost med izbranima vozliščema kompleksne mreže. Na prvem nivoju predstavljenega algoritma poiščemo obliko neenačbe, na drugem nivoju pa ustrezne koeficiente in odločitveni prag. Ocenitveno funkcijo, ki je ozko grlo predlaganega algoritma, smo implementirali na grafično procesni enoti s tehnologijo CUDA, s čimer dosežemo učinkovito vzporedno izvajanje. V eksperimentalnem delu doktorske disertacije pokažemo primernost predstavljenega algoritma za analizo naravnih kompleksnih mrež. V primerjavi z metodami strojnega učenja in evolucijskimi algoritmi dosežemo boljše rezultate. Doktorsko disertacijo zaključimo s pregledom opravljenega dela in ovrednotenjem našega prispevka na raziskovalnem področju.
Keywords:	evolucijski algoritmi, strojno učenje, kompleksne mreže, netopološke lastnosti vozlišč, funkcijski zapis, paralelno računanje, GPGPU, CUDA
Place of publishing:	Maribor
Publisher:	[D. Jesenko]
Year of publishing:	2018
PID:	20.500.12556/DKUM-69973
UDC:	004.421:519.254(043.3)
COBISS.SI-ID:	294829312
NUK URN:	URN:SI:UM:DK:LQBHNERN
Publication date in DKUM:	03.05.2018
Views:	1789
Downloads:	298
Metadata:
Categories:	KTFMB - FERI
:	JESENKO, David, 2018, Algoritem določanja funkcijske odvisnosti povezav med vozlišči v kompleksnih mrežah [online]. Doctoral dissertation. Maribor : D. Jesenko. [Accessed 12 April 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=69973 Copy citation

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Secondary language

Language:	English
Title:	An algorithm for determining the functional relation of nodes' connectivity in complex networks
Abstract:	In this Doctoral thesis, a new two-level evolutionary algorithm is introduced for defining the functional dependency between non-topological nodes' properties and complex networks' edges. The result of the algorithm is a threshold function, which determines connectivity between nodes in a complex network. A suitable function form is achieved at the first level, while the second level is used for an optimal function fitting. The evaluation function, which is a bottleneck of the proposed algorithm, is implemented on a general purpose graphic processing unit using CUDA. In that way, the parallelization of the algorithm is achieved. The suitability of the algorithm for complex network analysis is presented within the experimental part of the thesis. A comparison with machine learning and evolutionary algorithms showed the superiority of the proposed algorithm. Critical evaluation of the work done and addressing the main contributions of this work conclude the thesis.
Keywords:	evolutionary algorithms, machine learning, complex network, non-topological node properties, function definition, parallel computing, GPGPU, CUDA

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