Paper Title:
A Novel Intelligent Modeling Method for Wood Drying Process
  Abstract

This paper investigates the development and intelligent modeling problem for a wood drying kiln process via optimized support vector machine (SVM). Based on parameters optimization and model selection idea, the swarm intelligence algorithms of Particle Swarm Optimization (PSO)-SVM and Genetic Algorithm (GA)-SVM were proposed for wood drying process with strong coupling and nonlinear characteristics. The simulation results showed that both of these two kinds of swarm intelligence optimization algorithm could get the appropriate parameters of SVM effectively, and by contrast, PSO showed a better learning ability and generalization in wood drying process modeling, and could establish predictive model with better accessibility.

  Info
Periodical
Chapter
Chapter 2: Advanced Design Science (1)
Edited by
Dongye Sun, Wen-Pei Sung and Ran Chen
Pages
647-651
DOI
10.4028/www.scientific.net/AMM.121-126.647
Citation
D. Y. Zhang, C. Y. Zhang, L. K. Zhu, Z. D. Diao, "A Novel Intelligent Modeling Method for Wood Drying Process", Applied Mechanics and Materials, Vols. 121-126, pp. 647-651, 2012
Online since
October 2011
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