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Title:Primerjava različnih algoritmov po vzoru obnašanja netopirjev : diplomsko delo
Authors:Grajfoner, Žan (Author)
Fister, Iztok (Mentor) More about this mentor... New window
Brezočnik, Lucija (Co-mentor)
Files:.pdf VS_Grajfoner_Zan_2019.pdf (1,53 MB)
 
Language:Slovenian
Work type:Bachelor thesis/paper (mb11)
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomski nalogi smo se osredotočili na algoritme po vzorih iz narave. Opisujemo evolucijske algoritme, katerih navdih je bila Darwinova teorija o boju za obstanek, in algoritme inteligence roja, ki črpajo navdih iz obnašanja roja živali v naravi. Primerjali smo osnovni algoritem po vzoru obnašanja netopirjev in hibridno različico algoritma po vzoru obnašanja netopirjev. Raziskali smo razlike med osnovnima arhitekturama obeh algoritmov, pripadajoče parametre, kot tudi področja uporabe obeh algoritmov. Primerjavo smo izvedli na praktičnem primeru optimizacije desetih testnih funkcij na treh različnih dimenzijah problema (10, 20, 30). Prav tako smo raziskali vpliv različnih velikosti populacije (20, 30, 50) pri obeh algoritmih. Ugotovili smo, da so rezultati optimizacije hibridne različice algoritma boljši od standardne različice algoritma.
Keywords:algoritem po vzoru obnašanja netopirjev, evolucijski algoritmi, hibridizacija, inteligenca roja, računska inteligenca.
Year of publishing:2019
Place of performance:Maribor
Publisher:[Ž. Grajfoner]
Number of pages:VIII, 44 f.
Source:Maribor
UDC:004.421(043.2)
COBISS_ID:22577174 Link is opened in a new window
NUK URN:URN:SI:UM:DK:W86J3LE2
License:CC BY-NC-ND 4.0
This work is available under this license: Creative Commons Attribution Non-Commercial No Derivatives 4.0 International
Views:142
Downloads:36
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FERI
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Secondary language

Language:English
Title:A comparison between different bat algorithms
Abstract:In this thesis, we are focusing on nature-inspired algorithms. We describe evolutionary algorithms inspired by the Darwinian theory and swarm intelligence algorithms that have been inspired by the behaviour of swarms in nature. We compare the original bat algorithm with the hybrid bat algorithm and investigate the differences between the regular architecture of both algorithms, related parameters, and areas of use of both algorithms. In the experiment, we use ten benchmark functions on three different dimensions (10, 20, 30). We also research the influence of the population size (20, 30, 50) on both algorithms. Results show that the hybrid bat algorithm outperforms the standard bat algorithm.
Keywords:bat algorithm, evolutionary algorithms, hybridization, swarm intelligence, computational intelligence.


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