Sareh Naji - Department ofCivilEngineering,FacultyofEngineering,UniversityofMalaya,50603KualaLumpur,Malaysia
Shahaboddin Shamshirband - b Department ofComputerSystemand Technology,FacultyofComputerScienceandInformationTechnology,UniversityofMalaya,50603KualaLumpur,
Hossein Basser - c Department ofCivilandEnvironmentalEngineering,AmirkabirUniversityofTechnology,Tehran,Iran
Afram Keivani - Department ofCivilengineering,TabrizBranch,IslamicAzadUniversity,Tabriz,Iran

Thehugedemandforenergyandconstructionmaterialshasbecomeanissueofgreatconcernrecently.Theenergyusageofbuildingsaccountsforalargepercentageofthetotalprimaryenergyconsumption.Thetotalenergyrequirementofbuildingsisinfluencedbyvariousfactors,includingenvironmentalandclimaticconditions,buildingenvelopematerials,insulation,etc.Inthisrespect,estimatingtheoperationalenergyofbuildingsispotentiallyhelpfulforarchitectsandengineersintheearlydesignandconstructionstages.Inthisstudy,theadaptiveneurfuzzyinferencesystem(ANFIS)isdesignedandadaptedtoestimatetheenergyconsumptionofbuildingsaccordingtothemainbuildingenvelopeparameters,namelymaterialthicknessandinsulationKvalue.Upto180simulationsusingdifferentmaterialthicknessvaluesandinsulationpropertiesarecarriedoutinEnergyPlussoftwareinordertouseforestimation.ThissoftcomputingmethodologyisimplementedwithMatlab/Simulinkandtheper-formance isinvestigated.

Energy consumptionResidentialbuildingsEnergy efficiencyNeuro-fuzzyANFIS