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Title:Uporaba metod mehkega računanja v proizvodnih sistemih
Authors:ID Šafner, Jure (Author)
ID Balič, Jože (Mentor) More about this mentor... New window
ID Klančnik, Simon (Comentor)
Files:.pdf UN_Safner_Jure_2015.pdf (1,61 MB)
MD5: 2CE8E273D046D1A420760DB37EFDA8EE
 
Language:Slovenian
Work type:Undergraduate thesis
Typology:2.11 - Undergraduate Thesis
Organization:FS - Faculty of Mechanical Engineering
Abstract:V diplomskem delu smo raziskali in nazorno predstavili metode mehkega računanja in njihove prednosti. Pri tem smo se osredotočili na nevronske mreže, mehko logiko, evolucijsko računanje in skupinsko inteligenco. Vsako metodo smo raziskali in predstavili po naslednjem ključu: zgled v naravi, uporabnost v industriji, oblikovanje metode in njeni sestavni deli ter predstavitev delovanja metod. Nato smo na podlagi strokovne in znanstvene literature naredili primerjavo omenjenih metod. Z diplomskim delom smo potrdili, da so metode mehkega računanja koristna orodja za reševanje optimizacijskih problemov ter so uporabne pri kompleksnih NP problemih.
Keywords:mehko računanje, umetna inteligenca, nevronske mreže, genetski algoritmi, skupinska inteligenca, mehka logika, algoritem kolonije mravelj, inteligenca roja delcev.
Place of publishing:Maribor
Publisher:[J. Šafner]
Year of publishing:2015
PID:20.500.12556/DKUM-48363 New window
UDC:004.89(043.2)
COBISS.SI-ID:18883094 New window
NUK URN:URN:SI:UM:DK:3SPR7ZLN
Publication date in DKUM:02.07.2015
Views:2050
Downloads:150
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FS
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Secondary language

Language:English
Title:Application of soft computing techniques in manufacturing system
Abstract:In this Diploma thesis we discuss the benefits of soft computing to modern manufacturing processes. The focus has been put on neural networks, evolutionary algorithms, swarm intelligence and fuzzy logic. The explanation of each method consists of a comparison with the natural occurrence, the application of the method and its structure; it is illustrated by a simplified model/example of its application. Based on literature we are presenting a comparison between soft computing and conventional methods. Diploma thesis proves that soft computing is a useful tool for optimization and it can produce good results in resolving NP hard problems,
Keywords:soft computing, artificial intelligence, neural networks, genetic algorithms, swarm intelligence, fuzzy logic, ant colony algorithm, particle swarm optimisation


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