简介:基于平衡损失的思想和最小二乘统一理论,对带线性约束的一般线性模型提出了一种全面度量估计优良性的标准.给出了此标准下模型中回归系数线性函数的约束广义平衡LS估计,并得到了约束广义平衡LS估计唯一性的一个充分条件.
简介:Itiswellknownthatwhentherandomerrorsareiid.withfinitevariance,theweekandthestrongconsistencyofLSestimateofmultipleregressioncoefficientsareequivalent.Thisnote,byconstructingacounter-example,showsthatthisequivalencenolongerholdstrueincasethattherandomerrorspossessonlyther-thmomentwith1≤r<2.
简介:摘要随着电力调度的不断发展,对电网调度自动化系统的要求越来越高,对“四遥”数据的精准率要求也越来越高,因此电力调度自动化状态估计合格率的稳定已成为国家电网公司地区电网运行情况的主要考核指标。对于影响状态估计遥测合格率的根源、以及提高状态估计合格率的改进措施的研究变的刻不容缓。
简介:TheLS-SVM(Leastsquaressupportvectormachine)methodispresentedtosetupamodeltoforecasttheoccurrenceofthunderstormsintheNanjingareabycombiningNCEPFNLOperationalGlobalAnalysisdataon1.0°×1.0°gridsandcloud-to-groundlightningdataobservedwithalightninglocationsysteminJiangsuprovinceduring2007-2008.Adatasetwith642samples,including195thunderstormsamplesand447non-thunderstormsamples,arerandomlydividedintotwogroups,one(having386samples)formodelingandtherestforindependentverification.ThepredictorsareatmosphericinstabilityparameterswhichcanbeobtainedfromtheNCEPdataandthepredictandistheoccurrenceofthunderstormsobservedbythelightninglocationsystem.Preliminaryapplicationstotheindependentsamplesfora6-hourforecastofthunderstormeventsshowthatthepredictioncorrectionrateofthismodelis78.26%,falsealarmrateis21.74%,andforecastingtechnicalscoreis0.61,allbetterthanthosefromeitherlinearregressionorartificialneuralnetwork.
简介:SupportVectorMachine(SVM)isapowerfulmethodologyforsolvingproblemsinnon-linearclassification,functionestimationanddensityestimation,whichhasalsoledtomanyotherrecentdevelopmentsinkernelbasedmethodsingeneral.Thispaperpresentsahighaccuracyandfault-tolerantSVMforthemobilegeo-locationproblem,whichisanimportantcomponentofpervasivecomputing.Simulationresultsshowitsbasiclocationperformance,andillustrateimpactsofthenumberoftrainingsamplesandtrainingareaontestlocationerror.
简介:对各种工业产品进行跌落测试数值仿真是ANSYS/LS-DYNA程序的一个重要的应用领域。本文以个人数字助理(PDA,PersonalDigitalAssistant)的有限元跌落仿真分析为例,讨论了ANSYS/LS-DYNA跌落测试模块(DTM)提供的数值仿真分析方法及实现过程。