DocumentCode
527795
Title
Modeling stand density index based on artificial neural network
Author
Huang, Jiarong ; Gao, Guangqin ; Meng, Xianyu ; Guan, Yuxiu
Author_Institution
Coll. of Forestry, Henan Agric. Univ., Zhengzhou, China
Volume
4
fYear
2010
fDate
10-12 Aug. 2010
Firstpage
1734
Lastpage
1736
Abstract
A stand density index BP model was created with artificial neural network modeling technology, by taking the average of diameter at breast height as the input variable, and stand number density as the output variable, in Masson pine planted forest. Through training and optimum seeking, the idea model structure is 1:2:1, the fitting accuracy is 98.67%. As a comparison, a Reineke stand density index model was created and fitted with regression analysis method and same sample data, the fitting accuracy is 97.76%. The results comparing with BP model and Reineke model indicate that the artificial neural network is a more effective stand density index modeling technique.
Keywords
backpropagation; forestry; neural nets; regression analysis; BP model; Masson pine planted forest; Reineke stand density index model; artificial neural network modeling technology; regression analysis; Artificial neural networks; Biological system modeling; Data models; Fitting; Indexes; Mathematical model; Neurons; Pinus massoniana; artificial neural network; model; stand density index;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location
Yantai, Shandong
Print_ISBN
978-1-4244-5958-2
Type
conf
DOI
10.1109/ICNC.2010.5584350
Filename
5584350
Link To Document