Hybrid PSO Algorithm for Estimation Modulus of Elasticity of Wood

被引:0
|
作者
Li, Mingbao [1 ]
Zhang, Jiawei [2 ]
机构
[1] Northeast Forestry Univ, Sch Civil Engn, Harbin, Heilongjiang Pr, Peoples R China
[2] Northeast Forestry Univ, Sch Electromech Engn, Harbin, Heilongjiang Pr, Peoples R China
关键词
Modulus of elasticity of wood; neural network; particle swarm optimization;
D O I
10.1109/CIMSA.2009.5069959
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Particle swarm optimization algorithm based neural network construction has been presented to calibrate the complex nonlinear relationship between modulus of elasticity (MOE) and wood physical property parameters. Consider that the traditional BP algorithm has shortcomings of converging slowly and easily trapping a local minimum value, a hybrid algorithm using particle swarm optimization (PSO) and back propagation (BP) is adopted to train the neural network. Modeling and Simulation results show that the optimization technique based on PSO modeling method is feasible and effective, with high generalization ability of the model and forecast accuracy.
引用
收藏
页码:247 / +
页数:2
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