一類圖值過程不具有大團(tuán)聚性的一個(gè)充分條件.pdf

1、南京航空航天大學(xué)碩士學(xué)位論文一類圖值過程不具有大團(tuán)聚性的一個(gè)充分條件姓名：?jiǎn)绦⊙嗌暾?qǐng)學(xué)位級(jí)別：碩士專業(yè)：概率論與數(shù)理統(tǒng)計(jì)指導(dǎo)教師：耿顯民201012一類圖值過程不具有大團(tuán)聚性的一個(gè)充分條件IIAbstractInrecentyearscomplexwkshavesetoffawaveofdomesticfeignresearchhavebeenstronglyconcernedbytheresearchersinallareasfrom

2、thescienceengineering.ManyrealwldsystemscanbedescribedbycomplexwkssuchassocialwkstheWldWideWebtheIntersoon..FromthemathematicalpointofviewanywkcanbeabstractedasagraphconsistingofnodesetVedgesetEwherenodesrepresenttheelem

3、entsofthewkedgesrepresenttherelationshipbetweenelements.ManyevolutionwkmodelscanbeviewedasgraphvaluedMarkovprocesses.Differentfromtheclassicalromgraphprocessgraphvaluedstochasticprocessdiscussesthegraphprocesswherenodese

4、dgesvaryromly.Hereaddremovenodesromlyoverthetimewhenanodeisremovedtheedgeslinkingtoitarealsoremoved.Thescalefreebehavifthehighclusteringpropertyofthegraphvaluedprocessarethemainpropertythatpeopleareinterestedinespecially

5、thesufficientconditionfgraphvaluedprocesspossessingthepropertyreallycatchesresearchers’attention.Tofindoutfeaturesofthefmationmechanismofcomplexwksresearcheshaveproposemanymodelsofevolutionwks.Howeveruptodatethefeaturesr

6、esearchesofgraphvaluedprocessofevolutionmodelshavebeenremainedmostlyinnumericalsimulationthemeanfieldtheythemainequationsoonwhicharethemethodsofstatisticalphysicssomemodelsevenlackriglymathematically.Inthispaperwestudyth

7、egraphvaluedMarkovprocesswithnewnodesedgesfromtheperspectiovofstochasticanalysiswegetthesufficientconditionftheMarkovprocesseswhichdonotexpressthehighclusteringproperty.Keywds:complexwksgraphvaluedMarkovprocessclusteingc