免疫克隆选择算法及其在加热炉状态识别中的应用研究

Yaoguang Wei, Deling Zheng, Ying Wang
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引用次数: 2

摘要

本文提出的免疫克隆选择算法是受生物免疫应答机制的启发而提出的。它由抗原抗体匹配、克隆增殖、突变和记忆细胞选择四个步骤组成。它是一个自适应学习系统,抗体多样性来自克隆和突变过程,使系统具有自适应能力。它从抗体记忆细胞选择过程中积累知识。该方法参数少,易于稳定。讨论了该算法在加热炉状态识别中的应用,结果表明该模型具有良好的模式识别能力和数据压缩能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research of an immune clone selection algorithm and its application in heating furnace state recognition
The immune clone selection algorithm presented in this paper is inspired by the mechanism exhibited in biological immune response. It is made up of four procedures: antigen-antibody matching, clone proliferation, mutation and memory cell selection. It is a self-adaptive learning system, antibody diversity coming from clone and mutation process, and which make the system has self-adaptive capability. It accumulates knowledge from antibody memory cell selection process. It has few parameter and easy to stable. We discuss the application of the algorithm on state recognition of the heating furnace, the results show that the model has good ability on pattern recognition and data compress.
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