计算机应用 ›› 2013, Vol. 33 ›› Issue (03): 810-813.DOI: 10.3724/SP.J.1087.2013.00810

• 人工智能 • 上一篇    下一篇

改进克隆选择算法的收敛性分析

郑仙花,骆炎民*   

  1. 华侨大学 计算机科学与技术学院,福建 厦门361021
  • 收稿日期:2012-09-17 修回日期:2012-10-27 出版日期:2013-03-01 发布日期:2013-03-01
  • 通讯作者: 郑仙花
  • 作者简介:郑仙花(1989-),女,福建莆田人,硕士研究生,主要研究方向:人工智能、机器学习、图像处理; 骆炎民(1974-),男,福建惠安人,副教授,主要研究方向:人工智能、数据挖掘、机器学习。
  • 基金资助:

    福建省自然科学基金资助项目(2012J01273); 泉州市科技计划项目(2010Z53)。

Convergence analysis of improved clonal selection algorithm

ZHENG Xianhua, LUO Yanmin*   

  1. College of Computer Science and Technology, Huaqiao University, Xiamen Fujian 361021, China
  • Received:2012-09-17 Revised:2012-10-27 Online:2013-03-01 Published:2013-03-01
  • Contact: ZHENG Xian-hua

摘要: 为了完善克隆选择算法(CSA),使算法理论上成熟,利用两个随机收敛性度量:完全收敛和均值收敛, 证明基于多类数据分类的改进克隆选择算法(Multi_CSA)满足收敛到全局最优解的充分条件,并以实验数据进行验证。从理论上证明了Multi_CSA满足收敛的充分条件,实验方面也表明该算法在经过一定的代数后会收敛。理论和实验上均表明:Multi_CSA是一个能在有限代内收敛的较为成熟算法。

关键词: 人工免疫, 克隆选择, 分类, 收敛性

Abstract: In order to improve Clonal Selection Algorithm (CSA) and make it theoretically mature, this paper adopted two random convergence measures: complete convergence and mean convergence to do the convergence analysis for the proposed algorithm named improved clonal Selection Algorithm for Multi-class Classification (Multi_CSA). It demonstrated that the Multi_CAS satisfied the sufficient condition for convergence to a global optimal solution. An experiment was also performed to validate the result.The paper proves that Multi_CAS meets the sufficient condition for convergence.The experiment shows that the algorithm will converge after several generations.It is concluded that Multi_CSA can converge within limited generation and it is a relatively mature algorithm.

Key words: artificial immune, clonal selection, classification, convergence

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