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OALib Journal期刊
ISSN: 2333-9721
费用：99美元
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fruitflyoptimizationalgorithmbasedhighefficiencyandlownoxcombustionmodelingforaboiler
, PP. 25-30
Keywords: ultra？supercritical,1000mwunit,boiler,efficiency,noxemissions,supportvectormachine,fruitflyoptimizationalgorithm
Abstract:
inordertocontrolnoxemissionsandenhanceboilerefficiencyincoal？firedboilers,thethermaloperatingdatafromanultra？supercritical1000mwunitboilerwereanalyzed.onthebasisofthesupportvectorregressionmachine(svm),thefruitflyoptimizationalgorithm(foa)wasappliedtooptimizethepenaltyparameterc,kernelparametergandinsensitivelosscoefficientofthemodel.then,thefoa？svmmodelwasestablishedtopredictthenoxemissionsandboilerefficiency,andtheperformanceofthismodelwascomparedwiththatofthega？svmmodeloptimizedbygeneticalgorithm(ga).theresultsshowthefoa？svmmodelhasbetterpredictionaccuracyandgeneralizationcapability,ofwhichthemaximumaveragerelativeerroroftestingsetliesinthenoxemissionsmodel,whichisonly3.59%.theabovemodelscanpredictthenoxemissionsandboilerefficiencyaccurately,sotheyareverysuitableforon？linemodelingprediction,whichprovidesagoodmodelfoundationforfurtheroptimizationoperationoflargecapacityboilers.
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