文献类型：期刊文献

中文题名：DNA免疫遗传算法及其应用

英文题名：Research on DNA immune genetic algorithm and its application

作者：文欣秀[1];许光泞[2]

机构：[1]华东理工大学信息科学与工程学院,上海200237;[2]上海新华控制技术(集团)有限公司,上海200241

年份：2011

卷号：47

期号：26

起止页码：55

中文期刊名：计算机工程与应用

外文期刊名：Computer Engineering and Applications

收录：CSTPCD;;北大核心:【北大核心2008】；CSCD:【CSCD2011_2012】；

语种：中文

中文关键词：径向基函数(RBF)神经网络;DNA编码;DNA免疫遗传算法;T-S模糊模型

外文关键词：Radial Basis Function（RBF）neural network; DNA coding; DNA immune genetic algorithm; T-S fuzzy model

摘要：在研究T-S模糊RBF神经网络的基础上,提出了一种基于DNA生物机理和结构的免疫遗传算法,用于优化设计T-S模糊RBF神经网络的规则后件参数。该方法采用基于抗体浓度的更新策略调节机制,能有效地保持抗体的多样性,避免早熟收敛。应用于延迟焦化汽油干点的软测量建模,实例仿真结果表明DNA免疫遗传算法在T-S模糊神经网络系统的优化设计中是有效的,可获得较高精度的模型。
Having researched on the construct of T-S fuzzy RBF neural network,the method based on the DNA biology mechanism and structure is studied for optimizing the coefficient of the consequence of T-S fuzzy RBF neural network via the DNA immune algorithm.In this method,the adjusting mechanism based on antibody concentration updating strategy can keep the antibody diversity and avoid the premature convergence.It is used in soft-sensing modeling of the dry-point of gasoline delayed cooking.The experimental simulation results show that DNA immune algorithm is effective in the optimizing design of T-S fuzzy neural network system,and high accuracy model can be obtained.