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基于神经网络的中央空调遗传算法优化研究.docx

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基于神经网络的中央空调遗传算法优化研究为题目，写不少于1200的论文 Abstract Withtheincreasingdemandforenergy-savingandenvironmentalprotectioninbuildings,theoptimizationofcentralairconditioningsystemshasbecomeahotresearchtopic.Inthispaper,anoptimizationmethodbasedonneuralnetworkandgeneticalgorithmisproposedforcentralairconditioningsystems.Themethodcombinestheadvantagesofneuralnetworksinpatternrecognitionandlearningabilitywiththegeneticalgorithm'sglobalsearchabilityandoptimizationcapability.Theproposedmethodisappliedtotheoptimizationofacentralairconditioningsysteminacommercialbuilding,andtheresultsshowthattheproposedmethodcanimprovetheenergyefficiencyofthesystemcomparedwiththetraditionalcontrolmethod. Keywords:centralairconditioningsystemoptimization,neuralnetwork,geneticalgorithm,energyefficiency. 1.Introduction Centralairconditioningsystemsarewidelyusedinmanybuildingsandhavebecomeanimportantpartofmodernbuildingenergysystems.However,theenergyconsumptionofthesesystemsisstillveryhigh,accountingforasignificantproportionofthetotalenergyconsumptioninbuildings.Therefore,optimizingcentralairconditioningsystemshasgreatpotentialforenergy-savingandenvironmentalprotectioninbuildings. Traditionalcontrolmethodsforcentralairconditioningsystemsusuallyusefixedcontrolrulesorproportional-integral-derivative(PID)controllers.Thesemethodshavesomelimitationsintermsofenergyefficiencyandresponsespeed.Inrecentyears,manyresearchershaveproposedvariousoptimizationmethodsforcentralairconditioningsystems,suchasmodelpredictivecontrol(MPC),fuzzycontrol,andartificialneuralnetwork(ANN)control. Amongthesemethods,ANN-basedcontrolhasattractedmuchattentionduetoitspowerfulpatternrecognitionandlearningability.However,ANN-basedcontrolalonecannotensuretheglobaloptimalsolution,anditmayeasilyfallintolocaloptimalsolutions.Geneticalgorithm(GA)isaglobaloptimizationmethodthatcaneffectivelysolvethisproblem.Therefore,combiningANNandGAcanimprovetheperformanceofthecontrolsystem. Inthispaper,anoptimizationmethodbasedonneuralnetworkandgeneticalgorithm