identifying key variables and interactions in statistical models of building energy consumption using regularization

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1、Energy83(2015)144e155ContentslistsavailableatScienceDirectEnergyjournalhomepage:www.elsevier.com/locate/energyIdentifyingkeyvariablesandinteractionsinstatisticalmodelsofbuildingenergyconsumptionusingregularization*DavidHsu210S34thStreet,Philadelphia,PA19104,USAartic

2、leinfoabstractArticlehistory:Statisticalmodelscanonlybeasgoodasthedataputintothem.DataaboutenergyconsumptionReceived2September2014continuestogrow,particularlyitsnon-technicalaspects,butthesevariablesareofteninterpretedReceivedinrevisedformdifferentlyamongdisciplines

3、,datasets,andcontexts.Selectingkeyvariablesandinteractionsistherefore9January2015animportantstepinachievingmoreaccuratepredictions,betterinterpretation,andidentificationofkeyAccepted4February2015subgroupsforfurtheranalysis.Availableonline6March2015Thispaperthereforem

4、akestwomaincontributionstothemodelingandanalysisofenergycon-sumptionofbuildings.First,itintroducesregularization,alsoknownaspenalizedregression,forprin-Keywords:cipledselectionofvariablesandinteractions.Second,thisapproachisdemonstratedbyapplicationtoaEnergyconsumpt

5、ionBuildingscomprehensivedatasetofenergyconsumptionforcommercialofficeandmultifamilybuildingsinNewVariableselectionYorkCity.Usingcross-validation,thispaperfindsthatanewly-developedmethod,hierarchicalgroup-Statisticalmodelslassoregularization,significantlyoutperformsrid

6、ge,lasso,elasticnetandordinaryleastsquaresap-proachesintermsofpredictionaccuracy;developsaparsimoniousmodelforlargeNewYorkCitybuildings;andidentifiesseveralinteractionsbetweentechnicalandnon-technicalparametersforfurtheranalysis,policydevelopmentandtargeting.Thismeth

7、odisgeneralizabletootherlocalcontexts,andislikelytobeusefulforthemodelingofothersectorsofenergyconsumptionaswell.©2015TheAuthor.PublishedbyElsevierLtd.ThisisanopenaccessarticleundertheCCBYlicense(http://creativecommons.org/licenses/by/4.0/).1.Introductionincludingac

8、curatepredictions,theinterpretationofeffects,andidentificationofkeysubgroupsforfurtherphysics-basedmodelingStatisticalmodelsenableempirical