简介：

简介：AnewfilteringmethodforSARdatade-noisingusingwaveletsupportvectorregression(WSVR)isdeveloped.OnthebasisofthegreyscaledistributioncharacterofSARimagery,thelogarithmicSARimageasanoisepollutedsignalistakenandthenoisemodelassumptioninlogarithmicdomainwithGaussiannoiseandimpactnoiseisproposed.Basedonthebetterperformanceofsupportvectorregression(SVR)forcomplexsignalapproximationandthewaveletforsignaldetailexpression,thewaveletkernelfunctionischosenassupportvectorkernelfunction.ThenthelogarithmicSARimageisregressedwithWSVR.Furthermoretheregressiondistanceisusedasajudgmentindexofthenoisetype.Accordingtothejudgmentofnoisetypeeverypixelcanbeadaptivelyde-noisedwithdifferentfilters.Throughanapproximationexperimentforaone-dimensionalcomplexsignal,thefeasibilityofSARdataregressionbasedonWSVRisconfirmed.AfterwardtheSARimageistreatedasatwo-dimensionalcontinuoussignalandfilteredbyanSVRwithwaveletkernelfunction.Theresultsshowthatthemethodproposedherereducestheradarspecklenoiseeffectivelywhilemaintainingedgefeaturesanddetailswell.

简介：Thebuildingsectoranditsheatingandcoolingrepresentoneofthemajorconsumerofenergyworldwide.Simultaneously,theshareoffluctuatinggenerationofrenewableenergiesintheenergymixincreases.Thereforestorageanddemandsidemanagementtechnologiesarerequired.Thenewadaptiveandpredictivecontrolalgorithmforthermallyactivatedbuildingsystems(TABS)basedonmultiplelinearregression(AMLR)presentedinthispaperenablestheapplicationofdemandsidemanagement(DSM)strategies.Basedonsimulations,differentstrategieshavebeencomparedwitheachother.ByapplyingtheAMLRalgorithm,electricityenergycostsavingsof38%couldbeachievedcomparedtotheconventionalcontrolstrategyforTABS,whileincreasingthethermalcomfort.Atthesametime,thermalenergydemandcanbereducedintherangebetween4%to8%,andpumpoperationtimefrom86%to89%.