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基于改进Elman神经网络的林隙大小预测模型(PDF)

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

Issue:
2011年03期
Page:
5
Column:
研究论文
publishdate:
2011-06-13

Article Info:/Info

Title:
Model based on modified Elman neural network for forecasting forest gap size
Author(s):
FU Liyong1 HE Zheng2LIU Ying′an3*
1. Research Institute of Forest Resources information Techniques,CAF Beijing 100091,China;2.Forest Inventory and Planning Institute of Jiangxi Province,Nanchang 330046,China;3.College of Science,Nanjing Forestry University,Nanjing 210037,China
Keywords:
Elman neural network forest gap size simulation
Classification number :
S757
DOI:
10.3969/j.jssn.1000-2006.2011.03.006
Document Code:
A
Abstract:
A dynamic model for forecasting forest gap size was established using a modified Elman neural network for overcoming the disadvantage of timevariability, uncertainty, and complex nonlinear relationship with its impact factor of forest gap size. Firstly, the structural features, mathematical model and learning algorithm of the modified Elman neural network were examined, and a dynamic model for forecasting forest gap size was then set up based on the modified Elman neural network by selecting Larix principisrupprechtii, Spruce, Pinus tabulaeformis forest in Pangquangou Nature Reserve as the test objects. The fitting and simulation results showed that the established prediction model is feasible to forest gap size, and three kinds of forest gaps were lastly investigated using this model

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Last Update: 2011-06-13