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Title:SLUČAJNI GRAFI
Authors:ID Pasterk, Marko (Author)
ID Špacapan, Simon (Mentor) More about this mentor... New window
Files:.pdf UNI_Pasterk_Marko_2012.pdf (241,08 KB)
MD5: 9695C06BF220B7BD9DC45DE498B995D6
PID: 20.500.12556/dkum/d8d33769-bed3-44d6-b0ba-d061556733cc
 
Language:Slovenian
Work type:Undergraduate thesis
Organization:FNM - Faculty of Natural Sciences and Mathematics
Abstract:Diplomsko delo obravnava slučajne grafe. Osrednja tema so lastnosti, ki veljajo za skoraj vse grafe. V uvodnem delu so podane definicije iz verjetnosti in teorije grafov, ki jih potrebujemo v nadaljevanju diplomskega dela. V prvem poglavju s pomočjo matematičnega upanja določimo eno zgornjo in eno spodnjo mejo za dominantno število in neodvisnostno število grafa. Prav tako dokažemo obstoj grafa z velikim kromatičnim številom in velikim notranjim obsegom. V drugem poglavju sta predstavljena dva verjetnostna modela, s katerima opišemo lastnosti skoraj vseh grafov. Nekaj teh lastnosti tudi dokažemo. V zadnjem poglavju definiramo pragovne funkcije in določimo prag za lastnost obstoja izoliranih vozlišč v grafu G^p in za lastnost obstoja fiksnega grafa H kot podgraf v grafu G^p.
Keywords:slučajni graf, matematično upanje, Markova neenakost, verjetnostni model, pragovna funkcija, metoda drugega momenta
Place of publishing:Maribor
Publisher:[M. Pasterk]
Year of publishing:2012
PID:20.500.12556/DKUM-22739 New window
UDC:51(043.2)
COBISS.SI-ID:19136264 New window
NUK URN:URN:SI:UM:DK:S9KBG4YV
Publication date in DKUM:17.05.2012
Views:2329
Downloads:190
Metadata:XML DC-XML DC-RDF
Categories:FNM
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Secondary language

Language:English
Title:RANDOM GRAPHS
Abstract:The graduation thesis focuses on random graphs, in particular, we study properties of almost all graphs. In the introductory section definitions on probability theory and graph theory are given. In first chapter we use expectation to determine upper and lower bound for the domination number and the independence number of graph. We also prove the existence of graphs with large chromatic number and large girth. In second chapter there are presented two probability models that give us a way to describe properties of almost all graphs. In the last chapter we define threshold functions and determine the threshold for disappearance of isolated vertices in graph G^p and for appearance of isolated vertices of a fixed graph H as a subgraph of G^p.
Keywords:random graph, expectation, Markov’s inequality, probability model, threshold function, second moment method


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