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Multi-variable nonlinear BBMNN based Soft Sensor Modeling and Application

Of complex industrial processes, and can give better prediction results. The soft-sensor model is about to put into practical application of industrial processes. References [1] BhatNV, MindermarlPA, JetalMAT. Contro / Magaz / ne, 1990,3:24 [2] JosephB, BrosilowCB. MChEJounu71, 1978,24 (3): 485 [3] AndreasD, SebastianE, HorstR. IEEEControlSrst ~ Magazine, 1995,12 (10): 61 [4] WillisMJ, NassimoCD, JetalMA. IEEProcD, 1991,138 (3): 256 [5] MozerMC,[link widoczny dla zalogowanych], JordanMI, PetscheT, eds. Advances/nneurd678 afraid m0 mouth 'DnprooessingS ~ tem,[link widoczny dla zalogowanych],, 1997,9 ( Cool

: 134MoodyJE, HansonSJ, LippimnnRP. Advances / nneura / / rC'ormat / onprocessingsystems, 1992,4 (7): 847FreundY,[link widoczny dla zalogowanych], schap ~ RE. JounuT / ofJapaneseSo ~ yforArti woman with a gallery. 1999,14 (5): 771DruekerH. In: FisherJrDH, ed. PrDoeeoftheFour-teenfllIniemationdConferenceonMachinele jack iIlg, 1997.1o7 【9lKeamsM, ValiantLG. TechnicalReport1488, Canlobridge. MA: I-lavardUniversityAikenComputationLaborato-ry, 1988 [10] ScRE. Machine coffee, 1990,5:197 [11] Xiong Zhihua, Wang Xiong and so on. Control and Decision, 2OOO, 3:173 NonlinearSoftSensorModelingandApplicationUsingBoosting-・ BasedMultiplyNeuralNetworkChertFeng, GWeihua, LiYonggang, TangZhaohui (CollegeofInformationScience & El ~ ineering, CentralSouthUniversity, Changsha4xoo83) AbstractSoftwaresens0rhaeenconsideredfitsarIettlcienttooltodealwiththedimcul ~ ofimmeasurableprimaryoutput. Boostingisamethodforimprovingtheaccuracyofanygiver,[link widoczny dla zalogowanych], learning ~. orithm. Inthispaper, aimprovedadaboostalgo-rithmisintroduced. anda roar NeuralNetworkiscombinedwithu1ealgorithmtomodelanonlinearsoftsensor. 1Jsi. grimingdataofamulti. variable. nonlinearcomplexindustryprocess, thesimulationisdone. Theresultdemonstratesu1edtileness0fthemethod. KeyWOrdS; Boo6ting-basedmultiplyneuralnetwork, Nonlinear, Soft stern s0r, Boosting ・ --- 54 ・ ---

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