Research on DNA immune genetic algorithm and its application

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (26): 55-57.

• 研究、探讨 • Previous Articles Next Articles

Research on DNA immune genetic algorithm and its application

WEN Xinxiu1，XU Guangning2

1.College of Information Science and Engineering，East China University of Science and Technology，Shanghai 200237，China
2.Shanghai Xinhua Control Technology（Group） Co.，Ltd，Shanghai 200241，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-09-11 Published:2011-09-11

DNA免疫遗传算法及其应用

文欣秀1，许光泞2

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

Abstract

Abstract: 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.

Key words: 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。

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

WEN Xinxiu1，XU Guangning2. Research on DNA immune genetic algorithm and its application[J]. Computer Engineering and Applications, 2011, 47(26): 55-57.

文欣秀1，许光泞2. DNA免疫遗传算法及其应用[J]. 计算机工程与应用, 2011, 47(26): 55-57.

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Research on DNA immune genetic algorithm and its application

DNA免疫遗传算法及其应用

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