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Complex systems seen either in general engineering practice or economics are subjected to ever increased uncertainties that are mostly represented as random variables or parameters, and the characteristics of random variables are represented by their probability density functions (PDFs). Controlling their PDFs means to shape their stochastic distributions and in general it would provide a full treatment...
Time series predicting has become an important issue in many fields. The prediction methods which are based on the extreme learning machines have attracted many researchers. However, the predicted results of the extreme learning machines have some randomness. To obtain the better predicting performance and improve the randomness, we propose a new adaptive ensemble model of extreme learning machines...
A nonlinear model predictive control based on pseudolinear neural network (PNN) is proposed, in which the second order based optimization is adopted. The recursive computation of Jacobian matrix is also proposed. The stability analysis of the closed loop model predictive control system is presented based on Lyapunov theory. From the stability investigation, the sufficient condition for the asymptotic...
Due to the increasing cost of energy and the demand of reducing the environmental footprints, energy saving is becoming an important subject in the industry operation. To realize the energy consumption optimization of papermaking, the energy model should be established while the product quality and process model also need to be constructed, which are taken as the constraints for optimization. This...
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