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Deep learning has been proposed for soft sensor modeling in process industries. However, conventional deep neural network (DNN) is a static network and thereby can not embrace evident dynamics in processes. Motivated by nonlinear autoregressive with exogenous input (NARX) model and neural nets based dynamic modeling, a dynamic network called NARX-DNN is put forward by further utilizing historical...
Hinging hyperplanes (HH) is a kind of piecewise linear approximation methods which is proven to be effective for any continuous linear functions with arbitrary dimensions on compact sets in any given precision. In the open literatures, more attentions are concentrated on the representation capability and the convergence issue of parameter optimization is rarely concerned with, which is important for...
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