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A Comparison Study of MIMO Water Wall Model with Linear, MFNN and ESN Models

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dc.contributor.authorMoon, Un-Chul-
dc.contributor.authorLim, Jaewoo-
dc.contributor.authorLee, Kwang Y.-
dc.date.available2019-03-08T13:37:49Z-
dc.date.issued2016-03-
dc.identifier.issn1975-0102-
dc.identifier.issn2093-7423-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/7192-
dc.description.abstractA water wall system is one of the most important components of a boiler in a thermal power plant, and it is a nonlinear Multi-Input and Multi-Output (MIMO) system, with 6 inputs and 3 outputs. Three models are developed and comp for the controller design, including a linear model, a multilayer feed-forward neural network (MFNN) model and an Echo State Network (ESN) model. First, the linear model is developed by linearizing a given nonlinear model and is analyzed as a function of the operating point. Second, the MFNN and the ESN are developed by using training data from the nonlinear model. The, three models are validated using Matlab with nonlinear input-output data that was not used during training.-
dc.format.extent9-
dc.language영어-
dc.language.isoENG-
dc.publisherKOREAN INST ELECTR ENG-
dc.titleA Comparison Study of MIMO Water Wall Model with Linear, MFNN and ESN Models-
dc.typeArticle-
dc.identifier.doi10.5370/JEET.2016.11.2.265-
dc.identifier.bibliographicCitationJOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, v.11, no.2, pp 265 - 273-
dc.identifier.kciidART002084958-
dc.description.isOpenAccessN-
dc.identifier.wosid000370909800001-
dc.identifier.scopusid2-s2.0-84957074920-
dc.citation.endPage273-
dc.citation.number2-
dc.citation.startPage265-
dc.citation.titleJOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY-
dc.citation.volume11-
dc.type.docTypeArticle-
dc.publisher.location대한민국-
dc.subject.keywordAuthorWater wall model-
dc.subject.keywordAuthorPower plant modelling-
dc.subject.keywordAuthorPower plant identification-
dc.subject.keywordAuthorLinearization-
dc.subject.keywordAuthorMultilayer feed-forward neural network-
dc.subject.keywordAuthorEcho state network-
dc.subject.keywordPlusECHO STATE NETWORK-
dc.subject.keywordPlusSYSTEM-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
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