简介:Howtoefficientlymeasurethedistancebetweentwobasicprobabilityassignments(BPAs)isanopenissue.Inthispaper,anewmethodtomeasurethedistancebetweentwoBPAsisproposed,basedontwoexistingmeasuresofevidencedistance.Thenewproposedmethodiscomprehensiveandgeneralized.Numericalexamplesareusedtoillustratetheeffectivenessoftheproposedmethod.
简介:让G是有最大的度的一张连接的图3。我们为色彩的数字调查上面的界限<潜水艇class=“a-plus-plus”>力量图G的<啜class=“a-plus-plus”>。它被证明那\(\chi_\gamma(G)\leqslant\Delta\tfrac{{(\Delta-1)^\gamma-1}}{{\Delta-2}}+1=:M+1\),如果并且仅当G是一张穆尔图,平等在此成立。如果G不是,一张穆尔图,和G满足下列条件之一:(1)G是非常规的,(2)尺寸g(G)21,(3)g(G)2+2,并且连接(G)3如果3,(G)4但是g(G)>6如果=2,(4)比仅仅取决于的一个给定的数字足够地大,然后(G)M1。借助于光谱半径G的毗邻矩阵的1(G),它被看那2(G)1(G)2+1,如果并且仅当G与直径2和尺寸5是一颗星或一张穆尔图,平等在哪儿成立,并且(G)1(G)+13。
简介:Theaimofthispaperistodevelopanorderedweighteddistance(OWD)measure,whichisthegeneralizationofsomewidelyuseddistancemeasures,includingthenormalizedHammingdistance,thenormalizedEuclideandistance,thenormalizedgeometricdistance,themaxdistance,themediandistanceandthemindistance,etc.Moreover,theorderedweightedaveragingoperator,thegeneralizedorderedweightedaggregationoperator,theorderedweightedgeometricoperator,theaveragingoperator,thegeometricmeanoperator,theorderedweightedsquarerootoperator,thesquarerootoperator,themaxoperator,themedianoperatorandtheminoperatorarealsothespecialcasesoftheOWDmeasure.SomemethodsdependingontheinputargumentsaregiventodeterminetheweightsassociatedwiththeOWDmeasure.TheprominentcharacteristicoftheOWDmeasureisthatitcanrelieve(orintensify)theinfluenceofundulylargeorundulysmalldeviationsontheaggregationresultsbyassigningthemlow(orhigh)weights.ThisdesirablecharacteristicmakestheOWDmeasureverysuitabletobeusedinmanyactualfields,includinggroupdecisionmaking,medicaldiagnosis,datamining,andpatternrecognition,etc.Finally,basedontheOWDmeasure,wedevelopagroupdecisionmakingapproach,andillustrateitwithanumericalexample.
简介:将Lasso算法和logistic回归模型相结合并且引入P2P个人网络信贷评估体系,通过模拟实验的结果发现,在全变量logistic模型、Lasso-logistic模型、Ridge-logistic模型中,Lasso-logistic模型对于变量的压缩效果要更好,有助于简化模型;虽然三个模型在进行预测的结果上并没有显著的差异,但是Lasso-logistic模型在计算效率上更胜一筹,在处理大量数据的情况下更有效率。