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107 个结果
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  • 简介:Themotivationofdataminingishowtoextracteffectiveinformationfromhugedatainverylargedatabase.However,someredundantandirrelevantattributes,whichresultinlowperformanceandhighcomputingcomplexity,areincludedintheverylargedatabaseingeneral.So,FeatureSubsetSelection(FSS)becomesoneimportantissueinthefieldofdatamining.Inthisletter,anFSSmodelbasedonthefilterapproachisbuilt,whichusesthesimulatedannealinggeneticalgorithm.Experimentalresultsshowthatconvergenceandstabilityofthisalgorithmareadequatelyachieved.

  • 标签: 特征子集选择 遗传算法 模拟退火 数据挖掘 FSS
  • 简介:ANOVELDEFINITIONOFFORMFEATUREGaoFei;YeShanghuiANOVELDEFINITIONOFFORMFEATURE¥GaoFei;YeShanghuiAbstractBeinganessentialconcepti...

  • 标签: FEATURE FORM FEATURE featured PRIMITIVE ALGEBRAIC
  • 简介:Inthisnotewecharacterizethegeometricfactureofa(μ,r,k)-FES.Namely,foraC~μtriangularin-terpolationschcmewithC~rvertexdata,anyangleofthemacrotrianglemustbedividedintoatleast(μ+1)/(r+1-μ)parts.

  • 标签: VERTEX TRIANGULAR facture characterize SPLIT TRIANGLE
  • 简介:Inapplicationsoflearningfromexamplestoreal-worldtasks,featuresubsetselectionisimportanttospeeduptrainingandtoimprovegeneralizationperformance.Ideally,aninductivealgorithmshouldusesubsetoffeaturesassmallaspossible.Inthispaperhowever,theauthorsshowthattheproblemofselectingtheminimumsubsetoffeaturesisNP-hard.Thepaperthenpresentsagreedyalgorithmforreaturesubsetselection.Theresultofrunningthegreedyalgorithmonhand-writtennumeralrecognitionproblemisalsogiven.

  • 标签: 图象识别 感应学习 贪婪算法
  • 简介:Thispaperpresentsanovelapproachtofeaturesubsetselectionusinggeneticalgorithms.Thisapproachhastheabilitytoaccommodatemultiplecriteriasuchastheaccuracyandcostofclassificationintotheprocessoffeatureselectionandfindstheeffectivefeaturesubsetfortextureclassification.Onthebasisoftheeffectivefeaturesubsetselected,amethodisdescribedtoextracttheobjectswhicharehigherthantheirsurroundings,suchastreesorforest,inthecoloraerialimages.Themethodologypresentedinthispaperisillustratedbyitsapplicationtotheproblemoftreesextractionfromaerialimages.

  • 标签: 遗传算法 特征提取 分类结构 图像提取 交叉 变化
  • 简介:处理技术的计算机图象被用来在木头表面上完成缺点图象的特征抽取。由缺点的灰色的价值的计算。有用鉴别缺点被完成了的三个特征数据。实验显示那这样对木头表面上的缺点的自动化识别有效。

  • 标签: Binarilizaion GRAY IMAGE FEATURE EXTRACTION
  • 简介:Theanalysisoftheradiatednoiseofvesselsgiveninthispapershowssomestrongsuperposedlinecomponentsinlowfrequencyspeetrumbelow100Hzoccurringatdiscretefrequencieswhichcorrespondwiththerotationspeedofpropellershaft,orpropellerbladefrequency,ortheirharmonicfre-quencies.sincethelinecomponentsreflectpropeller'workingcharacteristics,thepropller'sfeaturescanbeextracteddirectlyfromlow-frequencylinecom-ponentsinadditiontodemodulatedlinecomponent.Sotherearetwowaystoextractthefeatures,oneisdirectway,theotherisdemodulationway.Detec-tionperformanceofthelinecomponentinbackground-noiseisdiscussedinthispaper.ThesignallevelisdefinedasthedifrerencebetweenthePDF's(ProbabilityDensityFunction)meanofthepeakofthelinecomponentandPDF'smeanorthebackground-noise.Indircetwaythesignallevelofthelinecomponentisproportionaltothesignalnoiseratio(S/N).Indemodulationwaythesignallevelofdemodulatedlinecomponent

  • 标签: Probability DEMODULATION normalized rotation correspond proportional
  • 简介:IntroductionDuringthelasttwodecadestherehavebeenremarkabledevelopmentsinEnglishlanguageteachinginChina.Withanever-increasingemphasisbeingputonthecommunicativecompetenceofthelearners,variousmethodsandtechniqueshavebeentriedtoimprovethestudents’abilitytocommunicateinEnglish.ThisarticlelooksatthevalueofusingWesternfeaturefilmstohelpstudentsdevelopthiscommunicativecompetence.

  • 标签: 多产
  • 简介:WegiveanintroductionforthebackgroundandmotivationoftheIntegratedPhotonics:ChallengesandPerspectivesfeature.Averybriefsummaryforthefiveinvitedreviewarticlescollectedinthisfeatureissueisalsogiven.

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  • 简介:特征定义的适应性是特征技术在设计过程成功应用的关键和核心问题.本文基于提出了面向设计过程的特征定义层次结构及特征定义方法,将特征定义用应用特征、形状特征和几何表示3个相对独立的层次来表示,并分别利用特征语义解释器和改进的几何关联图实现层次间的有效连接和相互转换,这不仅消弱了特征定义对应用的依赖性而更具广泛性,也为基于特征的并行设计过程模型的建立提供了基础.

  • 标签: 设计过程 特征建模 特征定义 分层构造
  • 简介:Translationinitiationsites(TISs)areimportantsignalsincDNAsequences.InmanypreviousattemptstopredictTISsincDNAsequences,threemajorfactorsaffectthepredictionperformance:thenatureofthecDNAsequencesets,therelevantfeaturesselected,andtheclassificationmethodsused.Inthispaper,weexaminedifferentapproachestoselectandintegraterelevantfeaturesforTISprediction.Thetopselectedsignificantfeaturesincludethefeaturesfromthepositionweightmatrixandthepropensitymatrix,thenumberofnucleotideCinthesequencedownstreamATG,thenumberofdownstreamstopcodons,thenumberofupstreamATGs,andthenumberofsomeaminoacids,suchasaminoacidsAandD.Withthenumericaldatageneratedfromthesefeatures,differentclassificationmethods,includingdecisiontree,naiveBayes,andsupportvectormachine,wereappliedtothreeindependentsequencesets.Theidentifiedsignificantfeatureswerefoundtobebiologicallymeaningful,whiletheexperimentsshowedpromisingresults.

  • 标签: 地点转换 CDNA 基因序列 信号传导
  • 简介:Traditionalsequenceanalysisdependsonsequencealignment.Inthisstudy,weanalyzedvariousfunctionalregionsofthehumangenomebasedonsequencefeatures,includingwordfrequency,dinucleotiderelativeabundance,andbase-basecorrelation.Weanalyzedthehumanchromosome22andclassifiedtheupstream,exon,intron,downstream,andintergenicregionsbyprincipalcomponentanalysisanddiscriminantanalysisofthesefeatures.Theresultsshowthatwecouldclassifythefunctionalregionsofgenomebasedonsequencefeatureanddiscriminantanalysis.

  • 标签: 染色体 分级 序列特征 分析
  • 简介:Inthispaper,afacialfeatureextractingmethodisproposedtotransformthree-dimension(3D)headimagesofinfantswithdeformationalplagiocephalyforassessmentofasymmetry.Thefeaturesof3Dpointcloudsofaninfant’scraniumcanbeidentifiedbylocalfeatureanalysisandatwo-phasek-meansclassificationalgorithm.The3Dimagesofinfantswithasymmetriccraniumcanthenbealignedtothesamepose.Themirroredheadmodelobtainedfromthesymmetryplaneiscomparedwiththeoriginalmodelforthemeasurementofasymmetry.Numericaldataofthecranialvolumecanbereviewedbyapediatriciantoadjustthetreatmentplan.Thesystemcanalsobeusedtodemonstratethetreatmentprogress.

  • 标签: 面部特征提取 不对称 婴儿 K-MEANS 3D图像 三维点云
  • 简介:Alotof3Dshapedescriptorsfor3Dshaperetrievalhavebeenpresentedsofar.Thispaperproposesanewmechanism,whichemploysseveralexistingglobalandlocal3Dshapedescriptorsasinput.Withthesparsetheory,somedescriptorswhichplaythemostimportantroleinmeasuringsimilaritybetweenquerymodelandthemodelinthedatasetareselectedautomaticallyandanaffinitymatrixisconstructed.Spectralclusteringmethodcanbeimplementedtothisaffinitymatrix.Spectralembeddingofthisaffinitymatrixcanbeappliedtoretrieval,whichintegratingalmostalltheadvantagesofselecteddescriptors.Inordertoverifytheperformanceofourapproach,weperformexperimentalcomparisonsonPrincetonShapeBenchmarkdatabase.Testresultsshowthatourmethodisapose-oblivious,efficientandrobustnessmethodforeithercompleteorincompletemodels.

  • 标签: 形状检索 形状匹配 特征描述 查询模型 形状描述 相似性测量