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非线性模型抗差最小二乘估计及其应用(PDF)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2005年03期
Page:
9-13
Column:
研究论文
publishdate:
2005-03-20

Article Info:/Info

Title:
The Least-squares Minimization Algorithm of Resisting Dimission Error on Application of Nonlinear Model
Article ID:
1000-2006(2005)03-0009-05
Author(s):
SHE Guang-hui1 LIU En-bin1 YE Jin-sheng2 LIN Shou-ming2
1. College of Forest Resources and Environment Nanjing Forestry University, Nanjing 210037, China; 2. Forestry Surveying and Designing Institute of Guangdong Province, Guangdong 510500, China
Keywords:
Dimission error The least-squares minimization algorithm of resisting error Resisted dimission error factor
Classification number :
TS653; TQ433
DOI:
10.3969/j.jssn.1000-2006.2005.03.003
Document Code:
A
Abstract:
This paper is based on the least-squares minimization algorithm and expound selectment of resisted dimission error factor. From resisting dimission error, this algorithm improves estimative precision of model. By using data of forest survey in Guangdong the paper introduces the method of the parametric identification of the model in detail. The result indicates that the algorithm has a great effect in resisting dimission error. In the course of collecting data,due to all kinds of causes, the data collected must have abnormity. If general leastsquares minimization algorithm was taken,the result of parametric identification have better resisting. In fitting model,general mothed is deleting abnormity using separated point graph, which need to do more work of data treatment. The new method of parametric identification with dimission error can overcome the difficulty and get the better estimation.

References

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Last Update: 2013-05-20