%0 Journal Article
%T Adaptive clone and suppression artificial immune algorithm<br>自适应克隆抑制人工免疫算法*
%A YANG Fu-gang
%A <br>杨福刚
%J 计算机应用研究
%D 2011
%I 
%X Analyzed the reasons of the traditional artificial immune algorithm easily falling into local extreme point or premature convergence in the optimization process. This paper put forward a novel artificial immune algorithm, adaptive clone and suppression artificial immune algorithm (ACSAIA). The algorithm took into account two factors of antibody affinity and concentration of antibody, and gave an adaptive operator to adjust them. Comparing with the corresponding evolutionary algorithm, ACSAIA could enhance the diversity of the population, avoid prematurity and solve deceptive problems to some extent. Meanwhile it had high convergence speed. The experiments show the proposed algorithm is superior to the traditional artificial immune algorithm and standard genetic algorithm in convergence speed and optimization performance.
%K antibody affinity
%K antibody
%K concentration
%K artificial immune algorithm(AIA)<br>抗体亲和度
%K 抗体浓度
%K 人工免疫算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=C3CC3D995F03C64801D870B7A8340FF5&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=0B39A22176CE99FB&sid=03436AC72A659ACA&eid=07C6E4664BB7C5DA&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=9