[1]左瑞娟,武永华.基于克隆选择的模糊分类规则提取算法[J].智能系统学报,2007,2(4):74-79.
ZUO Rui-juan,WU Yong-hua.Extracting fuzzy classification rules using clonal select ion algorithm[J].CAAI Transactions on Intelligent Systems,2007,2(4):74-79.
点击复制
ZUO Rui-juan,WU Yong-hua.Extracting fuzzy classification rules using clonal select ion algorithm[J].CAAI Transactions on Intelligent Systems,2007,2(4):74-79.
基于克隆选择的模糊分类规则提取算法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
2
期数:
2007年第4期
页码:
74-79
栏目:
学术论文—智能系统
出版日期:
2007-08-25
- Title:
- Extracting fuzzy classification rules using clonal select ion algorithm
- 文章编号:
- 16734785(2007)04007406
- 分类号:
- TP18
- 文献标志码:
- A
- 摘要:
- 分类是许多研究领域的关键问题，模糊规则的提取质量对分类器的性能又有着极大影响.所提取的规则不仅在分类能力上要达到最优，同时在规则数量上也不能太多，否则会影响规则搜索和匹配的速度.结合人工免疫的克隆选择原理，采用克隆选择算法，提取通过多精度模糊分割产生的大量模糊if-then规则中的少数精华规则，从而建立了模糊分类所需要的有效规则集合，同时还对优化目标函数进行了改进.经仿真实验证明，该方法所提取的模糊规则具有分类准确率高，规则数目较少等特点.
- Abstract:
- Classification is crucial for many research domains, but the quality o f extracted fuzzy rules has a great influence on the performance of classifiers. It is not only necessary that extracted rules have optimal performance in class ification, but also the number of rules must be as small as possible, otherwise, rule searching and matching becomes slow. In this paper, using the clone sele ction algorithm, the best rules were extracted from massive sets of fuzzy ifth e n rules generated from multiple precision fuzzy partitions. Thus a set of effect ive rules for fuzzy classification were developed. Also the optimal objective fu nction was improved. Test results prove that the proposed method uses fewer rul es and has high classification precision.
- 参考文献/References:
-
［1］ URSZULA M K, WOJCIECH T. Extraction of fuzzy rules from trained neuarl net wo rk using evolutionary algorithm［A］. ESANN’2003 Proceedings［C］. Brussels ,2003.
［2］TOKINAGA S, LU Jianjun, IKEDA Y. Neural network rule extraction by using t he genetic programming and its applications to explanatory classifications［J］. FundaMentals, 2005，88（10）：2627-2635.
［3］康胜武.基于粗糙集理论的属性处理方法和模糊规则提取及其应用研究［D ］.厦门：厦门大学，2001.
KANG Shengwu. Attribute treatment & fuzzy rules extraction and application r esearch based on rough set theory［D］. Xiamen:Xiamen University,2001
［4］MARGHNY M H,ELSEMMAN I E. Extracting fuzzy classification rules with g ene expression programming［A］. AIML’05 Conference ［C］.Cairo, Egypt, 2005.
［5］ISHIBUCHI H, NOZAKI K, TANAKA H. Distributed representation of fuzzy rules and its application to pattern classification［J］. Fuzzy Sets and Syst, 1994, 52(4):21-32.
［6］ISHIBUCHI H, NOZAKI K, YAMAMOTO N, et al.Selecting fuzzy ifthen rules for c lassification problems using genetic algorithms［J］. IEEE Trasactions on System s, 1995, 3(3):260-270.
［7］CASTRO L N, ZUBEN F J. Learning and optimization using the clonal selectio n principle［J］.IEEE Transactions on Evolutionary Computation,Special Issue on Ar tificial Immune Systems,2002,6(3):239-251.
［8］GEORGE A J T, GRAY D. Receptor editing during affinity maturation［J］. Im m Today, 1999,20(4): 196.
［9］BEREK C. ZIEGNER M. The maturation of the immune response［J］. Imm Toda y, 2002,14(8):400-402.
［10］NUSSENZWEIG M C. Immune receptor editing, revise and select［J］. C ell, 1998, 95(1):875-878.
备注/Memo
收稿日期：2006-11-23.
作者简介：
左瑞娟，女, 1975年生，讲师,主要研究方向为人工智能、计算智能、专家系统、模式识别.E-mail： zuoruijuan200002@163.com.
武永华，男，1975年生，讲师，主要研究方向为模式识别、单片机与嵌入式系统
更新日期/Last Update:
2009-05-07