应用灰色关系集群和cgnn分析矿井深部巷道围岩的稳定性控制 毕业论文外文翻译

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1、英文原文ApplicationofGreyRelationalClusteringandCGNNinAnalyzingStabilityControlofSurroundingRocksinDeepEntryofCoalMineWanbinYANG1,ZhimingQU2（1.BeijingUniversityofScienceandTechnology,Beijing,100083；2.HebeiUniversityofEngineering,Handan,056038）Abstract—Withcombinationofgreyneuralnetwork（CGN

2、N）andgreyrelationalclustering,themodelsareconstructed,whichareusedtosolvethepredictionandcoMParisonofsurroundingrocksstabilitycontrollingparametersindeepentryofcoalmine.TheresultsshowthatgreyrelationalclusteringisaneffectivewayandCGNNhasperfectabilitytobestudiedinashort-termprediction.

3、Combinedgreyneuralnetworkhasthefeaturesoftrendandfluctuationwhilecombiningwiththetime-dependentsequenceprediction.ItisconcludedthatgreatimprovementscoMParedwithanymethodsoftrendpredictionandsimplefactorincombinedgreyneuralnetworkisstatedanddescribedinstablycontrollingthesurroundingrock

4、sindeepentry.I.INTRODUCTIONGREYsystemtechnologystatestheuncertaintyofsmallsampleandpoorinformation.Withthedevelopmentandgenerationoftheunknowninformation,therealworldwillbediscoveredandthesystemoperationbehaviorwillbemasteredproperly.Throughoriginalstabilitywiththepre-processing,thegre

5、ysystemlawwillbedescribed.Thoughtherealworldisexpressedcomplicatedlyandthesatisfiedirregularly,theintegratedfunctionswillbeappearedasacertaininnerregularpattern[1].Thestudyingofgreysystemtechnologyisbasedonthepoorinformationwhichisgeneratedbypartsoftheknowninformationtoextractvaluables

6、tabilityandtoproperlyrecognizeandeffectivelycontrolthesystembehavior.Theneuralnetworkisdependentonitsinnerrelationstomodel,whichiswellself-organizedandself-adapted.Theneuralnetworkcanconquerthedifficultiesoftraditionallyquantitativepredictionandavoidthedisturbanceofman’smind.Thegreyrel

7、ationalanalysisisbasedonthesimilarityofgeometricparameterscurvetodeterminetherelationdegree.Thecloserthecurveshapesimilarityis,thegreaterthecorrespondingsequencecorrelationis.Thesimilarityisdescribedwithcorrelationcoefficientandcorrelationdegreewhichdescribestheeffectontheresultsbyva