感知重要点的期货时间序列模式识别的应用分析

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1、合肥工业大学硕士学位论文PerceptuallyImportantPoints-BasedFuturesTimeSeriesPatternRecognitionandItsApplicationResearchABSTRACTTimeseriesisanimportantclassoftemporaldataobjects,anditiseasytogetfromthetechnologyandfinancialapplication.Everydataofatimeseriesisobservedinchronologicalor

2、der,thenthetimeseriesisobtainedbyorderedthesedata.Thenatureoftimeseriesincludes:theamountofdataisverylarge,highdimensionsandmustbefrequentlyupdated.Inordertoeffectivelyminingtheimplicitknowledgeofthehistoricaldata,academicandindustrialcirclesuseavarietyoftechniquestore

3、ducethetimesequencecomplexity,andacommonlyusedmethodistoconvertthetimesequenceintoanotherkindofeasytounderstandtheimportantpointsmethodbasedonvisualexpression.Meanwhile,inordertoovercomethedimensiondisasteroftimeseriesdata,acorrespondingindexstructurethatbasedontheexpr

4、essingmethodisproposed.Aimedatidentifyingafuturestimeseriesdatasetwithcertaincharacteristicsandmoreeffectiveidentificationforsomekindofmodel,thisdissertationstudiesitsfeatureidentificationandindexingmethods.Themainresearchworkandachievementsareasfollows.(1)ProposetheZP

5、IP(ZigzagbasedPerceptuallyImportantPoints)importancepointrecognitionmethodbasedonZigzagperceptuallyimportantpoints.ThemethodisbasedonthePIP(PerceptuallyImportantPoints)method.Thealgorithmisoptimizedbythemaximumlocalmethodandstatebalancemethodtograduallyoptimizethelocal

6、lyimportantpoints,andmakeitmoreeffectiveidentificationfuturestimeseriesfeaturepoints.(2)PresenttheFIS(FeatureIndexStructure)featureindexmechanismbasedonthebinarysearchtreetosolvetheinefficientissueofrecognitionprocessinreal-time.Themethodisbasedonabinarysearchtree,inor

7、dertomoresuitableforfuturestimeseriesoffeaturerecognition,weimprovedalgorithmsbyintroducingtheconceptofimportantpointandtheprincipleoftheimportantpointsthathavelargerindexwillmorenearertherootnodeandgetagoodperformance.(3)PutforwardtheFZPIP(FeatureZigzagbasedPerceptual

8、lyImportantPoints)featurerecognitionmethodbasedonthefeatureZigzagperceptuallyimportantpointsbyintroducingthedefinitio