| 数据挖掘方法在树高模型建立中的应用 |
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| 引用本文： | 王冬.数据挖掘方法在树高模型建立中的应用[J].安徽农业科学,2010,38(16):8771-8774. |
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| 作者姓名： | 王冬 |
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| 作者单位： | 西南林业大学,云南昆明,650224 |
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| 摘 要： | 采用粗集理论求得以决策属性（树高）所对应的条件属性的最小简约集,并使用Apriori算法提取决策属性和条件属性的对应关系建立树高模型。与传统统计方法建立的树高模型相比,该模型具有较优的有效性和可行性。
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| 关 键 词： | 数据挖掘 粗糙集 树高模型 |
Application of Data Mining to Build Tree Height Models |
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| WANG Dong.Application of Data Mining to Build Tree Height Models[J].Journal of Anhui Agricultural Sciences,2010,38(16):8771-8774. |
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| Authors: | WANG Dong |
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| Institution: | WANG Dong(Southwest Forestry Univerciey,Kunming,Yunnan 650224) |
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| Abstract: | To use rough set theory and obtain the minimum simple set of condition attributes that corresponding to the decision-making attributes(height).The correspondence between the decision and conditions attributes was extracted using Apriori algorithm to establish the tree height model.The result of the former model has optimum effectiveness and feasibility comparing with that of traditional statistical methods tree height models. |
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| Keywords: | Data mining Rough set Tree height model |
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