| GA—BP网络在木材干燥过程建模中的应用 |
| |
| 引用本文： | 刘德胜,张佳薇.GA—BP网络在木材干燥过程建模中的应用[J].微计算机信息,2007,23(3X):217-219. |
| |
| 作者姓名： | 刘德胜 张佳薇 |
| |
| 作者单位： | [1]东北林业大学,黑龙江150040 [2]佳木斯大学,佳木斯,黑龙江154007 |
| |
| 基金项目： | 教育部科学技术研究重点项目（木材干燥过程计算机仿真及模糊智能控制系统的研究（01066） |
| |
| 摘 要： | 木材干燥是一个复杂的非线性系统，由于木材结构复杂且具有多样性和变异性，很难建立一个理想的符合木材干燥过程的数学模型。利用遗传算法的全局寻优能力优化BP神经网络连接权值系数，分别用BP和GA—BP两种算法建立了木材干燥基准模型。对比结果表明：GA—BP算法建立木材干燥基准模型提高了期望误差精度和收敛速度，避免了BP算法陷入局部极小值．预测平均误差为1．0413％，具有较好的预测精度。
|
| 关 键 词： | 木材干燥 遗传算法 神经网络 建模 |
| 文章编号： | 1008-0570（2007）03-3-0217-03 |
| 修稿时间： | 2007-02-032007-03-05 |
Application on the Identification of Wood Drying process Based on GA-BP |
| |
| LIU DESHENG ZHANG JIAWEI.Application on the Identification of Wood Drying process Based on GA-BP[J].Control & Automation,2007,23(3X):217-219. |
| |
| Authors: | LIU DESHENG ZHANG JIAWEI |
| |
| Affiliation: | 1.Northeast Forestry University, Harbin 150040, Heilongjiang;2.Jiamusi University, Jiamusi 154007, Heilongjiang |
| |
| Abstract: | For wood having variety, complexity and variability, wood drying process is a complicated nonlinear system, so it is difficult to get an ideal model for wood drying. The initial weights of BP neural network were evolved by the characteristics of global opti- mization of Genetic Algorithm, Lumber Moisture Content models are obtained with BP arithmetic and GA-BP arithmetic in this paper. Lumber Moisture Content models were obtained with BP arithmetic and GA-BP arithmetic, Training results showed that meansquare errors and accelerate of convergence were improved with GA-BP lumber moisture Content models, BP arithmetic immersion minim value was avoided, the prediction mean errors were 1.0413% and showed relatively high prediction precision. |
| |
| Keywords: | wood drying genetic algorithm neural network o Modeling |
| 本文献已被 维普 等数据库收录！ |
