Natural forest conservation hierarchical program with neural network |
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Authors: | Chuanwen Luo Jihong Li |
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Institution: | (1) College of Forestry, Northeast Forestry University, Harbin, 150040, China |
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Abstract: | In this paper, the implementing steps of a natural forest protection program grading (NFPPG) with neural network (NN) were
summarized and the concepts of program illustration, patch sign unification and regression, and inclining factor were set
forth. Employing Arc/Info GIS, the tree species diversity and rarity, disturbance degree, protection of channel system, and
classification management in the Maoershan National Forest Park were described, and used as the input factors of NN. The relationships
between NFPPG and above factors were also analyzed. By artificially determining training samples, the NFPPG of Moershan National
Forest Park was created. Tested with all patches in the park, the generalization of NFPPG was satisfied. NFPPG took both the
classification management and the protection of forest community types into account, as well as the ecological environment.
The excitation function of NFPPG was not seriously saturated, indicating the leading effect of the inclining factor on the
network optimization.
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Translated from Chinese Journal of Applied Ecology, 2005, 16(6): 1,002-1,006 译自: 应用生态学报, 2005, 16(6): 1,002–1,006] |
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Keywords: | neural network grade program natural forest protection program illustration inclining factor |
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