[1]陆建江,徐宝文,邹晓峰.模糊规则发现算法研究[J].东南大学学报(自然科学版),2003,33(3):271-274.[doi:10.3969/j.issn.1001-0505.2003.03.006]
 Lu Jianjiang,Xu Baowen,Zou Xiaofeng.Algorithms for discovering fuzzy rules[J].Journal of Southeast University (Natural Science Edition),2003,33(3):271-274.[doi:10.3969/j.issn.1001-0505.2003.03.006]
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模糊规则发现算法研究()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
33
期数:
2003年第3期
页码:
271-274
栏目:
自动化
出版日期:
2003-05-20

文章信息/Info

Title:
Algorithms for discovering fuzzy rules
作者:
陆建江12 徐宝文13 邹晓峰2
1 东南大学计算机科学与工程系,南京 210096; 2 解放军理工大学理学院,南京 210007; 3 武汉大学软件工程国家重点实验室,武汉 430072
Author(s):
Lu Jianjiang12 Xu Baowen13 Zou Xiaofeng2
1 Department of Computer Science and Engineering, Southeast University, Nanjing 210096, China
2 School of Science, PLA University of Science and Technology, Nanjing 210007, China
3 State Key Laboratory of Software, Wuhan University, Wuhan 430072, China
关键词:
模糊系统 模糊规则 快速算法 划分算法
Keywords:
fuzzy systems fuzzy rules fast algorithm partitioning algorithm
分类号:
TP18
DOI:
10.3969/j.issn.1001-0505.2003.03.006
摘要:
引入最小强度的概念来限制模糊属性集的搜索范围,提出一种能发现强模糊规则的快速算法.此算法利用Apriori算法的搜索技术来发现强模糊规则,因此具有较高的算法效率,并有效地解决了模糊系统的维数灾难问题.在快速算法的基础上,又提出一种能发现固定数目的强模糊规则的划分算法.该算法将数据库划分成多个子数据库,并在子数据库上通过发现划分强模糊属性集来限制全局强模糊属性集的搜索范围.实验表明,划分算法比快速算法更节省时间.
Abstract:
A minimum strength concept is introduced to restrict search range of fuzzy itemsets, and a fast algorithm for discovering strong fuzzy rules is provided. The fast algorithm uses search technology of Apriori algorithm to discover strong fuzzy rules, so it has high efficiency and solves effectively the curse of dimensionality in the fuzzy systems. In addition, a partitioning algorithm for discovering fixed strong fuzzy rules is also provided based on the fast algorithm. In the partitioning algorithm, database is partitioned into several sub-databases, and the partitioning strong fuzzy itemsets are discovered in sub-database to restrict search range of the whole strong fuzzy itemsets. The example shows that the partitioning algorithm can save more time than the fast algorithm.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目: 国家自然科学基金资助项目(60073012)、国家自然科学基金重点资助项目(69931040)、江苏省自然科学基金资助项目(BK2001004)、教育部高等学校骨干教师基金资助项目、江苏省科技攻关资助项目(BE2001025)、国家教育部博士点基金资助项目.
作者简介: 陆建江(1968—),男,博士后,副教授,ljj666@sina.com; 徐宝文(联系人),男,教授,博士生导师,bwxu@seu.edu.cn.
更新日期/Last Update: 2003-05-20