| 可变密度蓄积量的BP网络模型 |
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| 引用本文： | 张志,杨海周,孙玉军. 可变密度蓄积量的BP网络模型[J]. 河南林业科技, 2005, 25(1): 1-3 |
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| 作者姓名： | 张志 杨海周 孙玉军 |
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| 作者单位： | 1. 北京林业大学资源与环境学院,北京,100083
2. 林州市园林绿化管理处,河南,456500 |
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| 摘 要： | 在森林经营过程中,及时掌握森林资源的现状,预测其发展趋势对森林资源的宏观经营决策和管理十分重要。本文根据金沟岭林场的实际情况,采用人工神经网络方法建立了基于人工神经网络的混交林可变密度蓄积量BP网络模型,采用回归方程适应性检验法分别对模型的拟合效果进行适应性检验,检验结果表明所有模型是实用的,不存在系统偏差,表明用人工神经网络的方法对森林资源进行预测是可行的,可以满足林业生产经营的精度要求。
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| 关 键 词： | 人工神经网络 BP模型 森林资源 |
| 文章编号： | 1003-2630(2005)01-0001-03 |
| 修稿时间： | 2005-02-10 |
The BP Model for Variable Density Stand Volume |
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| ZHANG Zhi ,SUN Yu-jun. The BP Model for Variable Density Stand Volume[J]. Journal of Henan Forestry Science and Technology, 2005, 25(1): 1-3 |
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| Authors: | ZHANG Zhi SUN Yu-jun |
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| Affiliation: | ZHANG Zhi ~1,SUN Yu-jun ~1 |
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| Abstract: | In this article,the Jinggouling forest farm is taken as the research object. During the course of forest management, It is important to grasp the status in quo in time and predict the development trend of forest resources for macro-management decision. According to the practical condition in Jinggouling forest farm,the BP model for variable density stand volume was developed with the method of the artificial neural network. The test method of regression equation adaptability is used to test the simulative effects of models. The testing result indicates the model is practicable and no system deviation exist and shows The BP model can satisfy the precision of forestry production. |
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| Keywords: | Artificial neural network BP model Forest resources |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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