Abstract
The temperature-humidity models of wood drying were developed based on Time-delay neural network and the identification structures of Time-delay neural network were given. The controlling model and the schedule model, which revealed the relation between controlling signal and temperature-humidity and the relation between wood moisture content and temperature-humidity of wood drying, were separately presented. The models were simulated by using the measured data of the experimental drying kiln. The numerical simulation results showed that the modeling method was feasible, and the models were effective.
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Foundation item: This study was supported by the Key Program of Ministry of Education of China (01066).
Biography: ZHANG Dong-yan (1976–), female, Ph.D. candidate, associate professor in Northeast Forestry University, Harbin 150040, P.R. China.
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Zhang, Dy., Sun, Lp. & Cao, J. Modeling of temperature-humidity for wood drying based on time-delay neural network. J. of For. Res. 17, 141–144 (2006). https://doi.org/10.1007/s11676-006-0033-1
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DOI: https://doi.org/10.1007/s11676-006-0033-1