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In this paper, a novel wood moisture content prediction model is established via SVR (support vector regression) for drying process with severe nonlinear and coupling. The particle position and velocity of particle swarm optimization (PSO) algorithm is used to optimize the model parameters, so as to realize wood moisture content prediction. Simulation results of Quercus mongolica show that the PSO...
This paper investigates the development and evaluation of a intelligent control system for a wood drying kiln process incorporating DRNN (Diagonal Recurrent Network) and proportional-integral-derivative (PID) control such that the moisture content of lumber will reach and be stabilized at the desired set point. A description of the dynamics of the wood drying process by means of the DRNN is also presented...
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