简介:[篇名]Long-termtransitionofautomotivetechnologyfromviewpointof“motorfan”roadtest,[篇名]Mitigatingeffectondriverworkloadbylanetraceassist,[篇名]Modellingvehicledynamicsforvirtualexperimentation,roadtestsupportinganddynamiccontrol,[篇名]TechniqueforMeasuringDriver'sAttentionLevelbyUsingEvent-RelatedPotentials,[篇名]Theeffectofturbulenceonpeakandaveragepressuresonacardoor,[篇名]TheFirstJapaneseFCBustobeTestedontheRoad,[篇名]TheFordMotorCompanyspin-torsionalNVHtestfacility-2,[篇名]Torque-givenControlofSwitchedReluctanceMotorDriveSuitableforElectricVehicle。
简介:[篇名]ACIVILENGINEERINGMATERIALSCOURSEWAREWITHAVIRTUALLABORATORY,[篇名]Acompactsledsystemforlinearimpact,poleimpact,andsideimpacttesting,[篇名]ADynamicTestProcedureForAdhesivelyBondedComposite,[篇名]Alow-cost,high-performanceimpacttestfacility,[篇名]Amethodologyfortheidentificationofconstitutiveandcontactlawsofmetallicmaterialsunderhighstrainrates,[篇名]Amicro/macroimpacttestatcontrolledenergyforerosionandphase-transformationsimulation,[篇名]Aproactivesystemapproachtoautomotiveimpactdevelopment,[篇名]Astudyonfracturesurfaceofagedturbinerotorsteelbyfractaldimension,[篇名]AstudyonthedeterminationoffractureparametersfortherubbertoughenedpolymericmaterialswiththeinstrumentedCharpyimpacttest,[篇名]Anexaminationofthetaylorimpactproblemforexperimentsinvolvingsquareandcircularrods,[篇名]AnalysisoftestdataobtainedformCharpyVandimpacttensiletest,[篇名]Assessingthebeddingconditionsofsewerpipesusingeigenvibration,[篇名]Bucklingbehavioranalysisofarectangulartubestructurebylateralimpactload,[篇名]CHARACTERISTICEVALUATIONOFCFRPCOMPOSITESUNDERFALLINGWEIGHTIMPACTLOADING。
简介:Charpyimpacttestmodellingandlocalapproachtofracture,Comparisonofparamctricandnon-paramerricmcthocisfordetermininginjuryrish,CORRELATIONANALYSISOFAUTOMOBILECRASHRESPONSESBASEDONWAVELETDECOMPOSITIONS,Correlationstudyondifferentbumperimpacttestmethodandpredictedresults,Damagebehaiorinceramicplasma-coatedanduncoatedglasswithsteel-ballimpact。
简介:Dropimpacttest-mechanics&physicsoffailure;Drop-impactsimulationandexperimentalverificationforspindlefixationofvideoandaudiomodule;Ductile-brittletransitionevaluationofJapaneseswordandweldmetalsusingminiaturizedimpactspecimens;Dynamicbehaviorofhighpolymerswithfocusonamacrolon;DynamicJ{sub}Rcurvesof308stainlesssteelweldfrominstrumentedimpacttestofunprecrackedCharpyV-notchspecimens;Dynamicmechanicalanalysisandtougheningmechanismsofpolycarbonateand4,4'-dihydorxydiphenylcopolycarbonate;……
简介:短期光伏发电功率预测对维护电网安全稳定和协调资源利用具有重要意义,针对现有的神经网络法、小波分析法等单一预测模型预测精度提升有限的问题,引入集成学习的思想和方法,提出一种基于Stacking算法改进支持向量机(SVM)的短期光伏发电预测方法.该方法先使用多个不同的初级SVM对预测样本进行一次预测得到多个预测输出;然后对训练集进行聚类,使用与预测样本同类别的训练样本训练次级SVM;最后使用次级SVM对多个预测输出进行结合得到最终预测结果.经光伏发电系统的实际运行数据实验,结果表明本文提出的方法相较于单一预测模型精度有了明显提升.