Using Multi-input-layer Wavelet Neural Network to Model Product Quality of Continuous Casting Furnace and Hot Rolling Mill-中国Betway体育网页登陆

摘要 Anewarchitectureofwaveletneuralnetworkwithmulti-input-layerisproposedandimplementedformodelingaclassoflarge-scaleindustrialprocesses.Becausetheprocessesareverycomplicatedandthenumberoftechnologicalparameters,whichdeterminethefinalproductquality,isquitelarge,andtheseparametersdonotmakeactionsatthesametimebutworkindifferentprocedures,theconventionalfeed-forwardneuralnetworkscannotmodelthissetofproblemsefficiently.Thenetworkpresentedinthispaperhasseveralinput-layersaccordingtothesequenceofworkprocedureinlarge-scaleindustrialproductionprocesses.Theperformanceofsuchnetworksisanalyzedandthenetworkisappliedtomodelthesteelplatequalityofcontinuouscastingfurnaceandhotrollingmill.Simulationresultsindicatethatthedevelopedmethodologyiscompetentandhaswellprospectstothissetofproblems.

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Using Multi-input-layer Wavelet Neural Network to Model Product Quality of Continuous Casting Furnace and Hot Rolling Mill

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