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- W2386252355 abstract "System identification is a key link of system control. The appearance of neural network makes it solvable the problem of nonlinear dynamic system identification, which can hardly be solved by traditional i-dentification technology. Starting with simulation, with a heating boiler as a typical MIMO, nonlinear, dynamic , time - delayed industrial subject, boiler identification models based on dynamic BP and Elman networks are established, and error analysis is made for the identified results. The neural network is thus proved to possess broad prospects in the field of identification for boiler combustion system and its identification accuracy is rather high." @default.
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- W2386252355 date "2004-01-01" @default.
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- W2386252355 title "Application of neural network for boiler combustion system identification" @default.
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