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杜海峰

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期刊论文

Optimal approximation of linear systems by artificial immune response

杜海峰GONG Maoguo DU Haifeng & JIAO Licheng

Science in China: Series F Information Sciences 2006 Vol. 49 No.1 63-79,-0001,():

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摘要/描述

This paper puts forward a novel artificial immune response algorithm for optimal approximation of linear systems. A quaternion model of artificial immune response is proposed for engineering computing. The model abstracts four elements, namely, antigen, antibody, reaction rules among antibodies, and driving algorithm describing how the rules are applied to antibodies, to simulate the process of immune response. Some reaction rules including clonal selection rules, immunological memory rules and immune regulation rules are introduced. Using the theorem of Markov chain, it is proofed that the new model is convergent. The experimental study on the optimal approximation of a stable linear system and an unstable one show that the approximate models searched by the new model have better performance indices than those obtained by some existing algorithms including the differential evolution algorithm and the multi-agent genetic algorithm.

版权说明:以下全部内容由杜海峰上传于   2010年08月27日 14时48分44秒,版权归本人所有。

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