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基于免疫原理的数据流聚类算法 被引量：5

Data Stream Clustering Based on Immune Principle
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摘要 由于基于免疫的学习方法能够较好地适应数据流不断变化及高速处理的要求,本文据此提出一种基于免疫原理的数据流聚类算法(AIN-STREAM).该算法能够动态适应数据流的变化,并能有效抑制噪声.AIN-STREAM通过建立与维护B细胞特征向量,从而能够根据用户的要求自动调整B细胞的识别区域,保证聚类结果的稳定性.理论分析和实验结果表明,在聚类结果相当的条件下,AIN-STREAM具有比同类算法更高的时间与空间效率,同时具有较高的聚类精度. The learning based on immune principle adapts well to the dynamic environment, and thus it can be applied to the data stream processing which is dynamic and requires high-speed processing. Therefore, an algorithm of clustering data streams based on immune principle is proposed, namely AIN-STREAM. The proposed algorithm can track the evolving clusters on noisy data sets. AIN-STREAM is capable of adjusting the recognition zone of B-cells automatically according to the requirement of users by creating and maintaining the B-Cell feature vectors. Thus, the stability of the clustering result is ensured. Theoretical analysis and comprehensive experimental results demonstrate that AIN-STREAM is superior over other immune principle based clustering algorithms under the circumstance of similar clustering results. Moreover, the results show that AIN-STREAM has a high clustering quality.
作者 王述云 张成洪 郝秀兰 胡运发
机构地区 复旦大学计算机信息与技术系 福州大学公共管理学院 复旦大学信息管理与信息系统系
出处 《模式识别与人工智能》 EI CSCD 北大核心 2009年第2期246-255,共10页 Pattern Recognition and Artificial Intelligence
基金 国家自然科学基金资助项目(No.60736016 70471011)
关键词 免疫原理 数据流 聚类 特征向量 识别区域 Immune Principle, Data Stream, Clustering, Feature Vectors, Recognition Zone
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论]
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参考文献22

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  • 2Barbara D. Requirements for Clustering Data Streams. ACM SIGKDD Explorations Newsletter, 2002, 3 (2): 23 -27
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二级参考文献21

  • 1Aggarwal CC,Han J,Wang J,Yu PS.A framework for clustering evolving data streams.In:Freytag JC,Lockemann PC,Abiteboul S,Carey MJ,Selinger PG,Heuer A,eds.Proc.of the Int'l Conf.on Very Large Data Bases.Berlin:Morgan Kaufmann Publishers,2003.81-92
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共引文献60

同被引文献44

  • 1杜海峰,公茂果,刘若辰,焦李成.自适应混沌克隆进化规划算法[J].中国科学（E辑）,2005,35(8):817-829. 被引量：28
  • 2赵宇,李兵,李秀,刘文煌,任守榘.混合属性数据聚类融合算法[J].清华大学学报（自然科学版）,2006,46(10):1673-1676. 被引量：9
  • 3杨春宇,周杰.一种混合属性数据流聚类算法[J].计算机学报,2007,30(8):1364-1371. 被引量：22
  • 4陈崚,邹凌君,屠莉.多数据流的实时聚类算法[J].计算机应用,2007,27(8):1976-1979. 被引量：2
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  • 7Gong Maoguo, Jiao Licheng, Du Haifeng, et al. Muhiobjective Im- mune Algorithm with Nondominated Neighbor-Based Selection. Evo- lutionary Computation, 2008, 16 (2) : 225 - 255.
  • 8de Lemos R, Timmis J, Ayara, M, et al. Immune-Inspired Adapta- ble Error Detection for Automated Teller Machines. IEEE Trans on Systems, Man and Cybernetics, 2007, 37 (5) : 873 - 886.
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  • 10de Castro L N, von Zuben F J. An Evolutionary Immune Network for Data Clustering// Proc of the 6th Brazilian Symposium on Neural Networks. Rio de Janeiro, Brazil, 2000 : 84 - 89.

引证文献5

二级引证文献14

模式识别与人工智能
2009年 第2期

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