Modeling Wood Crystallinity with Multiple Linear Regression

机译：具有多个线性回归的木材结晶度建模

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The crystallinity,of wood has an important effect on the physical, mechanical and chemical properties of cellulose fibers. Crystallinity of larch plantation wood was investigated with near infrared spectroscopy and multiple linear regression. Five typical wave lengths were selected to establish prediction model for wood crystallinity. Full-cross validation was applied to the model development. The model performance is satisfied with prediction correlation coefficient of 0.896 and bias of 0.0004. The results indicated that prediction of wood crystallinity with near infrared spectroscopy and multiple linear regression is feasible, which provides a fast and nondestructive method for wood crystallinity prediction.

机译：木材的结晶度对纤维素纤维的物理，机械和化学性质具有重要影响。用近红外光谱和多元线性回归研究了落叶松人工林的结晶度。选择五种典型的波长来建立木材结晶度的预测模型。全交叉验证已应用于模型开发。预测相关系数为0.896，偏差为0.0004，模型性能令人满意。结果表明，利用近红外光谱和多元线性回归预测木材的结晶度是可行的，为木材结晶度的预测提供了一种快速而无损的方法。

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来源
《Materials engineering for advanced technologies》|2011年|p.550-555|共6页
会议地点 Singapore(SG);Singapore(SG)
作者
Yaoxiang Li; Lichun Jiang;
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作者单位

College of Engineering and Technology, Northeast Forestry University, Harbin, Heilongjiang, P. R. China;

College of Forestry, Northeast Forestry University, Harbin, Heilongjiang, P. R. China;

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原文格式 PDF
正文语种 eng
中图分类工程材料一般性问题;
关键词
multiple linear regression; wood crystallinity; near infrared spectroscopy;

机译：多元线性回归;木材结晶度近红外光谱;

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Modeling Wood Crystallinity with Multiple Linear Regression

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