简介：Satisfactoryresultscannotbeobtainedwhenthreedimensional(3D)targetswithcomplexmaneuveringcharacteristicsaretrackedbythecommonlyusedtwo-dimensionalcoordinatedturn(2DCT)model.Toaddresstheproblemof3Dtargettrackingwithstrongmaneuverability,onthebasisofthemodifiedthree-dimensionalvariableturn(3DVT)model,anadaptivetrackingalgorithmisproposedbycombiningwiththecubatureKalmanfilter(CKF)inthispaper.Throughideologyofreal-timeidentification,theparametersofthemodelarechangedtoadjustthestatetransitionmatrixandthestatenoisecovariancematrix.Therefore,statesofthetargetarematchedinreal-timetoachievethepurposeofadaptivetracking.Finally,foursimulationsareanalyzedindifferentsettingsbytheMonteCarlomethod.Allresultsshowthattheproposedalgorithmcanupdateparametersofthemodelandidentifymotioncharacteristicsinreal-timewhentargetstrackingalsohasabettertrackingaccuracy.

简介：以便完成聪明的车辆的侧面的控制，基于云模型使用双性人认知的模型并且遮蔽推理，解决决定问题聪明的车辆的侧面的控制质、量。由驾驶车辆获得很多个实验数据，根据数据的概念分类数据并且修理云控制器的输入和输出变量，设计聪明的车辆的云控制器的控制规则，并且遮蔽并且修理云控制器的参数：期望，熵和亢奋的熵。以便验证云控制器的有效性，联合模拟站台基于Matlab/Simulink/CarSim被建立。试验性的分析显示出那：司机侧面的控制器基于云模型能完成需要的角度追踪，并且完成好控制效果，它也验证那一系列心理活动象感到那样，认知，计算，决定等等模糊、不明确。

简介：未预见到的活动数据爆炸象一样光谱资源姿势少见对今天的性能的主要挑战在新奇解决方案的迫切需要处理如此的多卷的活动数据的细胞的网络。长期进化放纵(LTE-U)，它扩大给没有执照的乐队动手术的LTE标准，被建议了改进系统产量。在LTE-U系统，到达用户们将与无线忠实(WiFi)竞争放纵的光谱资源播送数据信息的用户。不过，至于用为LTE用户的没有执照的乐队的传播的好处没有清楚的一致。到这个目的，在这份报纸，一个分析模型基于一个队列系统被介绍理解考虑服务(QoS)和LTE-U用户行为的质量的放纵的基于的LTE系统完成的性能。获得队列系统的替代状态答案，一个矩阵几何方法被用来解决它。然后，为LTE-U用户的没有执照的乐队的平均延期和利用被使用排队模型导出。LTE-U共存的表演用建议模型与WiFi被评估并且在实践至于LTE-U的优点提供一些起始的卓见。

简介：Thedegradationdataofmulti-componentsinmissileisderivedbyperiodicaltesting.Howtousethesedatatoassessthestoragereliability(SR)ofthewholemissileisadifficultproblemincurrentresearch.AnSRassessmentmodelbasedoncompetitionfailureofmulti-componentsinmissileisproposed.Byanalyzingthemissilelifeprofileanditsstoragefailurefeature,thekeycomponentsinmissileareobtainedandthecharacteristicsvoltageisassumedtobeitskeyperformanceparameter.Whenthevoltagetestingdataofkeycomponentsinmissileareavailable,astatespacemodel(SSM)isappliedtoobtainthewholemissiledegradationstate,whichisdefinedasthemissiledegradationdegree(DD).AWienerprocesswiththetime-scalemodel(TSM)isappliedtobuildthedegradationfailuremodelwithindividualvariabilityandnonlinearity.TheWeibulldistributionandproportionalriskmodelareappliedtobuildanoutburstfailuremodelwithperformancedegradationeffect.Furthermore,acompetitionfailuremodelwiththecorrelationbetweendegradationfailureandoutburstfailureisproposed.Anumericalexamplewithasetofmissilesinstorageisanalyzedtodemonstratetheaccuracyandsuperiorityoftheproposedmodel.

简介：Analgorithmofhighlymaneuveringtargettrackingisproposedtosolvetheproblemoflargetrackingerrorcausedbystrongmaneuver.Inthisalgorithm,anewestimator,namedasmulti-parameterfusionSinger(MF-Singer)modelisderivedbasedontheSingermodelandthefuzzyreasoningmethodbyusingradialaccelerationandvelocityofthetarget,andappliedtotheproblemofmaneuveringtargettrackinginstrongmaneuveringenvironmentandoperatingenvironment.ThetrackingperformanceoftheMF-Singermodelisevaluatedandcomparedwithothermanueveringtrackingmodels.ItisshownthattheMF-Singermodeloutperformsthesealgorithmsinseveralexamples.

简介：Inthispaper,weproposeadynamicmulti-descriptorfusion(DMDF)approachtoimprovingtheretrievalaccuracyof3-dimensional(3D)modelretrievalsystems.First,anindependentretrievallistisgeneratedbyusingeachindividualdescriptor.Second,weproposeanautomaticrelevant/irrelevantmodelsselection(ARMS)approachtoselectingtherelevantandirrelevant3Dmodelsautomaticallywithoutanyuserinteraction.Aweighteddistance,inwhichtheweightassociatedwitheachindividualdescriptorislearntbyusingtheselectedrelevantandirrelevantmodels,isusedtomeasurethesimilaritybetweentwo3Dmodels.Furthermore,adescriptor-dependentadaptivequerypointmovement(AQPM)approachisemployedtoupdateeveryfeaturevector.Thissetofnewfeaturevectorsisusedtoindex3Dmodelsinthenextsearchprocess.Four3DmodeldatabasesareusedtocomparetheretrievalaccuracyofourproposedDMDFapproachwithseveraldescriptorsaswellassomewell-knowninformationfusionmethods.ExperimentalresultshaveshownthatourproposedDMDFapproachprovidesapromisingretrievalresultandalwaysyieldsthebestretrievalaccuracy.

简介：Thisresearchisaimedtodevelopaconsumerdemandingsideresponsemodeltoassistelectricityconsumerstomitigatepeakdemandsduringthepeakseason.Themaincontributionofthisresearchisshowingthatconsumerscanmitigatepeakdemandsbyoptimizingenergycostsofanairconditioner(AC)whenaspikehappens.Itmayonlyoccurinaoneandahalfhoursspikeduringthepeakseason.ThismodelalsoinvestigateshowACappliesthepre-coolingmethodwhenthereisasubstantialriskofapricespike.Theresultsindicatethatthepotentialbenefitofthemodelisachievingenergysavingsforconsumersandaggregators,alsoreducingelectricitybillsfortheconsumers.Themodelistestedwithselectedcharacteristicsoftheroom,andbasedonthestandardroominaresidentialhouseinMakassar,acityofIndonesia.

简介：一个改进方法被建议模仿骚乱介绍的焕发，基于有限Markov州的模型。作为到文学的一个对比，一致地分布式的变量发生在某个状态期间，它比传统的Markov模型与更少状态贡献紧张变化的相等的模拟。它的也发现有20个状态的建议Markov模型在汽车协变性分析提供令人满意的近似给试验性的结果。而且，停止概率和吝啬的褪色时间是比有相等的状态的传统的Markov模型的那些更精确的。