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Ge, L. and Chen, G.-S. (2014) Control Modeling of Ash Wood Drying Using Process Neural Networks. Optik-International Journal for Light and Electron Optics, 125, 6770-6774. https://doi.org/10.1016/j.ijleo.2014.07.091

has been cited by the following article:

• TITLE: System Identification of Wood Drying Process Based on ARMAX Model

  AUTHORS: Zheng Zhou, Pinxiu Zhang, Baofu Huai, Liping Huang

  KEYWORDS: Wood Drying, System Identification, Moisture Content

  JOURNAL NAME: Agricultural Sciences, Vol.10 No.3, March 11, 2019

  ABSTRACT: This article presents system identification of wood drying process based on ARMAX model. Temperature and equivalent moisture content are considered as inputs, and moisture content of the wood sample during drying is taken as output of the system. The comparative study of RLS and FF-RLS to identify the system parameters is presented. Simulation results are presented to val-idate the efficacy of the ARMAX model for wood drying process.