Regressionanalysisisoneofthestatisticalmethodsusedfor developingmodelsforpredictionofenergyconsumptioninbuildings.
Thispaperpresentsrelevantinformationtounderstandandapply linearregressionanalysisforapplicationontheresidentialsectorwith focusonwhole-buildingenergyconsumptioninsingle-familyhomes. The energysignaturesandconditionaldemandanalysisarealso discussedforbetterunderstandingoftheuseofpracticalapplications of regressionanalysisforresidentialenergyconsumptionprediction. The literaturereviewofpapersdealingspecificallywithresidential energyconsumptionusingregression analysissupportsthefeasibility of thisstatisticalapproachformodel development.Thebasicsofsimple and multiplelinearregressionanalysiswereappliedtodatafromthe TxAIREResearchandDemonstrationHouse#1,asacasestudy,to illustrateanexampleofresultsfromregressionanalysis.Asillustrated fromtheresultsofthecasestudy,asthetimeintervaloftheobserved data increases,thequalityofthemodelsimproves.Thisisexplainedby the factthatforlongertimeperiods,thediscrepanciesamong individualeffectsinshortertimeperiodsareaveragedoverlonger time periods.Thesolarradiationasasecondpredictorvariableshows improvementofthecoefficient ofdetermination,butdeterioratesthe rootmeansquareerror,whichjustifies theimportanceofusingboth parameterstoassessthequalityofthemodelbasedonthedeveloper's criteria.SinceHVACsystemsaccountsforalargeportionofthetotal energyconsumptionofbuildings,andbecausetheperformanceof HVACsystemscanbemodeledasasecondorderpolynomial,a quadraticregressionmodelcanofferbetterresultsforshortertime intervalssuchasanhour.Thisisnotnecessarilytrueforlongertime periodssuchasadaybecausethequadratictrendoftheHVACsystem is lost.
Regressionanalysisisoneofthestatisticalmethodsusedfor developingmodelsforpredictionofenergyconsumptioninbuildingsThispaperpresentsrelevantinformationtounderstandandapply linearregressionanalysisforapplicationontheresidentialsectorwith focusonwhole-buildingenergyconsumptioninsingle-familyhomes Discussedforbetterunderstandingoftheuseofpracticalapplications energysignaturesandconditionaldemandanalysisarealso ของ regressionanalysisforresidentialenergyconsumptionprediction Analysissupportsthefeasibility energyconsumptionusingregression literaturereviewofpapersdealingspecificallywithresidential thisstatisticalapproachformodel พัฒนา Thebasicsofsimple และ TxAIREResearchandDemonstrationHouse #1, asacasestudy, multiplelinearregressionanalysiswereappliedtodatafromthe เพื่อ illustrateanexampleofresultsfromregressionanalysis Asillustrated fromtheresultsofthecasestudy เพิ่มข้อมูล asthetimeintervaloftheobserved, thequalityofthemodelsimproves Thisisexplainedby factthatforlongertimeperiods, thediscrepanciesamong individualeffectsinshortertimeperiodsareaveragedoverlonger เวลารอบระยะเวลา Ofdetermination Thesolarradiationasasecondpredictorvariableshows improvementofthecoefficient, butdeterioratesthe rootmeansquareerror เงื่อนไข whichjustifies theimportanceofusingboth parameterstoassessthequalityofthemodelbasedonthedeveloper Energyconsumptionofbuildings SinceHVACsystemsaccountsforalargeportionofthetotal, andbecausetheperformanceof HVACsystemscanbemodeledasasecondorderpolynomial, quadraticregressionmodelcanofferbetterresultsforshortertime intervalssuchasanhour Thisisnotnecessarilytrueforlongertime periodssuchasadaybecausethequadratictrendoftheHVACsystem หายไป
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regressionanalysisisoneofthestatisticalmethodsusedfor developingmodelsforpredictionofenergyconsumptioninbuildings .
thispaperpresentsrelevantinformationtounderstandandapply linearregressionanalysisforapplicationontheresidentialsectorwith focusonwhole buildingenergyconsumptioninsingle familyhomes .การ energysignaturesandconditionaldemandanalysisarealso discussedforbetterunderstandingoftheuseofpracticalapplications ของ regressionanalysisforresidentialenergyconsumptionprediction . การ literaturereviewofpapersdealingspecificallywithresidential energyconsumptionusingregression analysissupportsthefeasibility การพัฒนา thisstatisticalapproachformodel .และ thebasicsofsimple multiplelinearregressionanalysiswereappliedtodatafromthe txaireresearchanddemonstrationhouse # 1 , asacasestudy , illustrateanexampleofresultsfromregressionanalysis . asillustrated fromtheresultsofthecasestudy asthetimeintervaloftheobserved , เพิ่มข้อมูลที่ factthatforlongertimeperiods thequalityofthemodelsimproves.thisisexplainedby ,thediscrepanciesamong ช่วงเวลา individualeffectsinshortertimeperiodsareaveragedoverlonger . thesolarradiationasasecondpredictorvariableshows improvementofthecoefficient ofdetermination butdeterioratesthe , rootmeansquareerror , whichjustifies theimportanceofusingboth parameterstoassessthequalityofthemodelbasedonthedeveloper เกณฑ์sincehvacsystemsaccountsforalargeportionofthetotal energyconsumptionofbuildings andbecausetheperformanceof , hvacsystemscanbemodeledasasecondorderpolynomial , quadraticregressionmodelcanofferbetterresultsforshortertime intervalssuchasanhour . thisisnotnecessarilytrueforlongertime
periodssuchasadaybecausethequadratictrendofthehvacsystem หายไป
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