| 粗糙集理论及其应用与发展研究 |
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| 引用本文： | 韦良.粗糙集理论及其应用与发展研究[J].数字社区&智能家居,2008(10):172-174. |
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| 作者姓名： | 韦良 |
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| 作者单位： | 同济大学电子与信息工程学院,上海201804 |
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| 摘 要： | 粗糙集理论是一种研究不精确、不确定性、处理不完备知识的数学工具，目前被广泛应用于人工智能、模式识别、机器学习、决策支持和数据挖掘等领域。该文通过介绍粗糙集理论及特点，叙述了粗糙集理论在各领域的应用发展情况，并且展望了其未来发展趋势。
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| 关 键 词： | 粗糙集 属性约简 粗糙集应用 数据挖掘 |
Rough Set Theory and Its Application Research |
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| WEI Liang.Rough Set Theory and Its Application Research[J].Digital Community & Smart Home,2008(10):172-174. |
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| Authors: | WEI Liang |
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| Affiliation: | WEI Liang (Electronics and Information School, Tongji University, Shanghai 201804, China) |
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| Abstract: | Rough set theory is a math theory which processes non-accurate, uncertain and incomplete knowledge. Currently, it has already been applied successfully in the area of Artificial Intelligence, Pattern Recognition, Machine Learning, Decision Analyzing and Data Mining etc. This paper introduces the rough set theory and its characteristics, reviews the development of this theory in different fields, and suggests evolutional trend in the coming future. |
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| Keywords: | rough set attribute reduction rough set application data mining |
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