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Journal of Artificial Intelligence and Data Mining، جلد ۸، شماره ۳، صفحات ۴۱۷-۴۲۵
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عنوان انگلیسی Identification of Multiple Input-multiple Output Non-linear System Cement Rotary Kiln using Stochastic Gradient-based Rough-neural Network
چکیده انگلیسی مقاله Because of the existing interactions among the variables of a multiple input-multiple output (MIMO) nonlinear system, its identification is a difficult task, particularly in the presence of uncertainties. Cement rotary kiln (CRK) is a MIMO nonlinear system in the cement factory with a complicated mechanism and uncertain disturbances. The identification of CRK is very important for different purposes such as prediction, fault detection, and control. In the previous works, CRK was identified after decomposing it into several multiple input-single output (MISO) systems. In this paper, for the first time, the rough-neural network (R-NN) is utilized for the identification of CRK without the usage of MISO structures. R-NN is a neural structure designed on the base of rough set theory for dealing with the uncertainty and vagueness. In addition, a stochastic gradient descent learning algorithm is proposed for training the R-NNs. The simulation results show the effectiveness of proposed methodology.
کلیدواژه‌های انگلیسی مقاله Cement Rotary Kiln, Rough-Neural Network, Stochastic Gradient Descent Learning, System Identification, Uncertainty
نویسندگان مقاله Gh. Ahmadi |
Department of Mathematics, Payame Noor University, Tehran, Iran.

M. Teshnelab |
Control Engineering Department, Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran.

نشانی اینترنتی http://jad.shahroodut.ac.ir/article_1804_39ce137f280721b29917428bca02e180.pdf
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