Artificial immune algorithm based on biological immune clone selection and immune network theory
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摘要: 提出一種基于生物免疫系統克隆選擇機理和免疫網絡理論的免疫算法.該算法通過抗體的克隆選擇和變異過程,完成對入侵抗原的清除,實現免疫防御的功能;利用免疫網絡調節的思想選擇抗體記憶細胞,完成知識的學習和積累,實現免疫自穩的功能;利用所建立的抗體記憶矩陣實現對類似入侵抗原的快速應答,行使免疫監視識別功能.該算法利用生物變異機制實現抗體的自適應調節,使系統具有自適應、自學習能力.在加熱爐狀態識別的應用研究表明,本文所提出的算法在解決數據識別方面具有較好的效果.Abstract: The paper proposed an immune algorithm based on the mechanism exhibited in biological immune clone selection and the immune network theory. The algorithm eliminates antigen by clone selection and mutation, accumulates knowledge by selection of antibody memory cells which inspired by the immune network theory, and realizes immune homeostasis. The function of antibody memory cells is immune surveillance. The self-adaptation of antibody is realized by the immune mutation mechanism, which makes the algorithm self-learning and self-adaptive. The results of an application study on the pattern recognition of heat furnaces shows that the algorithm has good abilities of pattern recognition and data compress.
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Key words:
- artificial immune /
- clone selection /
- self-adaptation /
- pattern recognition
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