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Lamarckian Clonal Selection Algorithm based function optimization

  • Xidian University

科研成果: 期刊稿件会议文章同行评审

2 引用 (Scopus)

摘要

Based on Lamarckism and Immune Clonal Selection Theory, Lamarckian Clonal Selection Algorithm (LCSA) is proposed in this paper. In the novel algorithm, the idea that Lamarckian evolution described how organism can evolve through learning, namely the point of "Gain and Convey" is applied, then this kind of learning mechanism is introduced into Standard Clonal Selection Algorithm (SCSA). Through the experimental results of optimizing complex multimodal functions, compared with SCSA and the relevant evolutionary algorithm, LCSA is more robust and has better convergence.

源语言英语
页(从-至)91-98
页数8
期刊Lecture Notes in Computer Science
3512
DOI
出版状态已出版 - 2005
已对外发布
活动8th International Workshop on Artificial Neural Networks, IWANN 2005: Computational Intelligence and Bioinspired Systems - Vilanova i la Geltru, 西班牙
期限: 8 6月 200510 6月 2005

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