A Composite Index-based Approach for Hierarchical Assessment of Forest Ecosystem Health: An Example of Pinus Tabulaeformis

Author(s):  
Mingxia Zhang ◽  
Dexiang Wang ◽  
Zhao Xu ◽  
Qiuju Guo
2013 ◽  
Vol 663 ◽  
pp. 823-826
Author(s):  
Shu Rong Hui ◽  
Xiao Xiao Dai ◽  
Hui Liu ◽  
Qiang Liu

Based on the basic theory of the forest ecosystem, we build the index system to evaluate forest ecosystem health from the stand-scale and take advantage of improved BP neural network to evaluate the ecosystem health of Larix Kaempferi plantation in the Liaodong area quantitatively. And then we analyze the stand-scale health grade status according to different slope aspect, forest age, average tree height and altitude. The results indicate that we make the satisfactory process to research the complex forest ecosystem using the improved BP neural network. The improved BP neural network which uses the momentum-adaptive learning rate adjustment algorithm and L-M learning rules decreases iteration times, makes the convergence speed very fast and improve the precision.


2002 ◽  
Vol 13 (2) ◽  
pp. 147-150
Author(s):  
Chen Gao ◽  
Wang Qing-li ◽  
Deng Hong-bing ◽  
Dai Li-min

2001 ◽  
Vol 7 (4) ◽  
pp. 214-228 ◽  
Author(s):  
Paul G. Schaberg ◽  
Donald H. DeHayes ◽  
Gary J. Hawley

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