一种用于模式识别的新型人工免疫系统模型的研究

Jose Lima Alexandrino, E. Filho
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引用次数: 13

摘要

通过人体生理学研究发现的新功能有助于人工免疫系统的进化。目前的工作通过观察自然免疫行为来研究一种新的体系结构,对于已知算法的应用有助于提高性能。本文考虑了一种将抗体有组织地分组的登机方式,从进化的过程来看,属于这些分组的抗体可以提高对特定抗原的适应性免疫应答。因此,同一类的抗体在同一组中。其他技术,如克隆,MLP和K-NN来比较这个新模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation of a New Artificial Immune System Model Applied to Pattern Recognition
The discovery of new functionalities through the study of human physiology has contributed toward the evolution of Artificial Immune Systems. The present work investigates a new architecture through observations of natural immunological behavior, for which application to known algorithms contributed toward an improved performance. This paper considers a boarding where the antibodies are grouped in an organized way and from an evolutionary process the antibodies that belong to these groupings can improve the adaptive immune reply to a determined antigen. Thus, antibodies of the same class are in the same grouping. Others techniques were implemented such as Clonalg, MLP and K-NN to compare this new model.
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