6.FUZZYINFERENCESIFK15037,3credits

YUITAARUMSARI,S.Kom,M.Komyuita@ub.ac.id

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HISTORY

YuitaArumSari,S.Kom,M.Kom 2

ProfessorLoKiA.Zadeh

In1965,Lo,iA.ZadehoftheUniversityofCaliforniaatBerkeleypublished"FuzzySets,"whichlaidoutthemathemaJcsoffuzzysettheoryand,byextension,fuzzylogic.ZadehhadobservedthatconvenJonalcomputerlogiccouldnotmanipulatedatathatrepresentedsubjecJveorvagueideas,sohecreatedfuzzylogictoallowcomputerstodeterminethedisJncJonsamongdatawithshadesofgray,similartotheprocessofhumanreasoning.hNp://www.cs.berkeley.edu/~zadeh/

ExampleofApplicaPons

MasseyUniversity3

•  InthecityofSendaiinJapan,a16-staJonsubwaysystemiscontrolledbyafuzzycomputer(SeijiYasunobuandSojiMiyamotoofHitachi)–therideissosmooth,ridersdonotneedtoholdstraps

•  Nissan–fuzzyautomaJctransmission,fuzzyanJ-skidbrakingsystem•  CSK,Hitachi–Hand-wriJngRecogniJon•  Sony-Hand-printedcharacterrecogniJon•  Ricoh,Hitachi–VoicerecogniJon•  Tokyo’sstockmarkethashadatleastonestock-tradingporKoliobasedon

FuzzyLogicthatoutperformedtheNikkeiexchangeaverage•  NASAhasstudiedfuzzycontrolforautomatedspacedocking:simulaJons

showthatafuzzycontrolsystemcangreatlyreducefuelconsumpJon•  Canondevelopedanauto-focusingcamerathatusesacharge-coupled

device(CCD)tomeasuretheclarityoftheimageinsixregionsofitsfieldofviewandusetheinformaJonprovidedtodetermineiftheimageisinfocus.Italsotrackstherateofchangeoflensmovementduringfocusing,andcontrolsitsspeedtopreventovershoot.

IntroducPonofFIS

IndianInsPtuteofTechnologyDelhi4

● AFuzzyInferenceSystem(FIS)isawayofmappinganinputspacetoanoutputspaceusingfuzzylogic

● FIS uses a collecJon of fuzzy membership funcJonsandrules,insteadofBooleanlogic.

● The rules in FIS (someJmes may be called as fuzzyexpertsystem)arefuzzyproducJonrulesoftheform:− ifpthenq,wherepandqarefuzzystatements.

● Forexample,inafuzzyrule− ifxislowandyishighthenzismedium.− Here x is low; y is high; z is medium are fuzzystatements;xandyareinputvariables;zisanoutputvariable,low,high,andmediumarefuzzysets.

IntroducPonofFIS(cont.)

IndianInsPtuteofTechnologyDelhi5

● The antecedent describes towhat degree the ruleapplies, while the conclusion assigns a fuzzyfuncJontoeachofoneormoreoutputvariables.● Most tools for working with fuzzy expert systemsallowmorethanoneconclusionperrule.● Thesetofrulesinafuzzyexpertsystemisknownasknowledgebase.

StructureofFuzzyExpertSystems

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KnowledgeBase

InferenceEngine

FuzzificaPon

DefuzzficaPon

Crispvalue

Crispvalue

FuncPonalProcess

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FuzzyficaPon

FuzzyLogicOperaPon

ImplicaPon

AgregaPon

DefuzzyficaPon

INPUT

OUTPUT

CrispvalueàfuzzymembershipfuncJon

AntecedentmaybejoinedbyOR;ANDoperators

FuzzyficaPon

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Fuzzyfikasi:prosesmemetakannilaicrisp(numerik)kedalamhimpunanfuzzydanmenentukanderajatkeanggotaannyadidalamhimpunanfuzzy.Halinidilakukankarenadatadiprosesberdasarkanteorihimpunanfuzzysehinggadatayangbukandalambentukfuzzyharusdiubahkedalambentukfuzzy.

Example:FuzzyficaPon

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Example:FuzzyficaPon

Sumber:SriKusumaDewi/AplikasiLogikaFu7zzy10

FuzzyMembershipFuncPon

FuzzyLogicwithEngineeringApplicaJons:TimothyJ.Ross11

TypesofMembershipFuncJons•ThemostcommonlyusedinpracJceare–Triangles–Trapezoids–Bellcurves–Gaussian,and–Sigmoidal

FuzzyMembershipFuncPon

FuzzyLogicwithEngineeringApplicaJons:TimothyJ.Ross12

FuzzyMembershipFuncPon

FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall13

FuzzyMembershipFuncPon

FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall14

FuzzyMembershipFuncPon

FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall15

FuzzyMembershipFuncPon

FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall16

FuzzyMembershipFuncPon

FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall17

FuzzyMembershipFuncPon

FuzzyLogic:Intelligence,Control,andInformaJon,J.YenandR.Langari,PrenJceHall18

FuzzyLogicOperaPon

Sumber:SriKusumaDewi/AplikasiLogikaFu7zzy19

Jikabagianantesendendihubungkanolehkonektorand,or,dannot,makaderajatkebenarannyadihitungdenganoperasifuzzyyangbersesuaian

ImplicaPon

Sumber:SriKusumaDewi/AplikasiLogikaFu7zzy20

ImplicaPon

Wikipedia21

ImplicaPon

Sumber:SriKusumaDewi/AplikasiLogikaFu7zzy22

AggregaPon

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AggregaPon

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AggregaPon

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AggregaPon

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AggregaPon

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AggregaPon

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AggregaPon

Mathworks29

DefuzzyficaPon

Mathworks30

DefuzzyficaPon

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•  Strategiyangumumdipakaidalamdefuzzifikasiadalahmenentukanbentukkompromiterbaik.

•  Metode-metodeuntukstrategiiniadalah:1.  Metodekeanggotaanmaximum(max-membership)2.  Metodepusatluas(CenterofArea,CoA).3.  Metodekeanggotaanmaksimumrata-rata(Mean-max

MembershipatauMiddle-of-Maxima)

DefuzzyficaPon

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DefuzzyficaPon

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DefuzzyficaPon

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YuitaArumSari,S.Kom,M.Kom 48

Thank