简介:Greyself-organizingmap(GSOM)modelisproposedandappliedinthedetectionofintrusion.ThroughtheimprovementoftheweightadjustmentusingtheGRC(greyrelationalcoefficient),thetrainingresultsofSOMgetbetter.Inthedetectionofdenyofservice(DOS)attacks,thismodelcanconsidertherelativityofthedatasetofDOSattacks.Finally,theexperimentsontheDOSdatasetconfirmtheirvaliditiesandfeasibilitiesoverthisGSOMmodel.
简介:Integrationofsoilinformationsystem(SIS)andinteractiveself-organizingdata(ISODATA)wasstudiedtoestablishproperagriculturaldevelopingzonesinredsoilregionofsouthernChinawhichareofcrucialimportancetofarmers,researchers,anddecisionmaderswhileutilizingandmanagingredsoilresources.SIScreatedbyusingARC/INFOwasusedtoprovidedataacquisition,systematicmodelparameterassignment,andvisualdisplayofanalyticresults.Topography,temperature,soilcomponent(e.g.,organicmatterandpH)andconditionofagriculturalproductionwereselectedasparametersofISODATAmodel.TakingLongyouCounty,ZhejiangProvinceasthecasestudyarea,theeffectoftheintegrationandrecommendationsarediscussedforfutureresearch.
简介:Microarraytechnologycanbeemployedtoquantitativelymeasuretheexpressionofthousandsofgenesinasingleexperiment.Ithasbecomeoneofthemaintoolsforglobalgeneexpressionanalysisinmolecularbiologyresearchinrecentyears.Thelargeamountofexpressiondatageneratedbythistechnologymakesthestudyofcertaincomplexbiologicalproblemspossible,andmachinelearningmethodsareexpectedtoplayacrucialroleintheanalysisprocess.Inthispaper,wepresentourresultsfromintegratingtheself-organizingmap(SOM)andthesupportvectormachine(SVM)fortheanalysisofthevariousfunctionsofzebrafishgenesbasedontheirexpression.Themostdistinctivecharacteristicofourzebrafishgeneexpressionisthatthenumberofsamplesofdifferentclassesisimbalanced.WediscusshowSOMcanbeusedasadata-filteringtooltoimprovetheclassificationperformanceoftheSVMonthisdataset.
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