| 数据挖掘研究现状及发展趋势 |
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| 引用本文： | 王惠中,彭安群.数据挖掘研究现状及发展趋势[J].工矿自动化,2011,37(2):29-32. |
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| 作者姓名： | 王惠中 彭安群 |
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| 作者单位： | 兰州理工大学电气工程与信息工程学院;甘肃省工业过程先进控制重点实验室,甘肃兰州,730050 |
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| 基金项目： | 甘肃省教育厅科研项目，国家自然科学基金 |
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| 摘 要： | 从数据挖掘的定义出发,介绍了数据挖掘的神经网络法、决策树法、遗传算法、粗糙集法、模糊集法和关联规则法等概念及其各自的优缺点;详细总结了国内外数据挖掘的研究现状及研究热点,指出了数据挖掘的发展趋势。
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| 关 键 词： | 数据挖掘 挖掘算法 神经网络 决策树 粗糙集 模糊集 研究现状 发展趋势 |
Existing Situation of Data Mining Research and Its Development Tendency |
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| WANG Hui-zhong,PENG An-qun.Existing Situation of Data Mining Research and Its Development Tendency[J].Industry and Automation,2011,37(2):29-32. |
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| Authors: | WANG Hui-zhong PENG An-qun |
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| Affiliation: | 1,2)(1.College of Electrical and Information Engineering of Lanzhou University of Technology,Lanzhou 730050,China.2.Key Laboratory of Gansu Advanced Control for Industrial Processes,Lanzhou 730050,China) |
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| Abstract: | From the definition of data mining,the paper introduced concepts and advantages and disadvantages of neural network algorithm,decision tree algorithm,genetic algorithm,rough set method,fuzzy set method and association rule method of data mining,summarized domestic and international research situation and focus of data mining in details,and pointed out the development trend of data mining. |
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| Keywords: | data mining algorithm of data mining neural network decision tree rough set fuzzy set research situation development tendency |
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