By use of immune evolutionary algorithm, a new optimal method of fuzzy controller was presented.
利用免疫进化算法，提出了一种新的模糊控制器优化设计方法。
In accordance with biological immune-system characteristics the authors have come up with a method of self-tuning PID controller parameters on the basis of an immune evolutionary algorithm.
根据生物免疫系统特性，提出了一种基于免疫进化算法的PID控制器参数自整定方法。
Aiming at the design difficulty for fuzzy neural network controller, an immune evolutionary algorithm is proposed to design the parameters of a radial basis function fuzzy neural network controller.
针对模糊神经网络控制器难于设计的问题，提出了一种免疫进化算法用于径向基函数模糊神经网络控制器参数的优化设计。
Based on immune evolutionary algorithm, a novel radial basis function (RBF) designing algorithm, the immune RBF (IRBF) network, was proposed.
基于免疫进化算法，提出了一种设计径向基函数(RBF)网络的新算法——免疫径向基函数网络(IRBF)训练算法。
Immune evolutionary algorithm will be used in the process of solving the model parameters.
在模型参数的求解过程中将用到免疫进化算法。
Immune evolutionary algorithm is a new optimization algorithm inspired by biological immune mechanism based on the deep understanding of the existing evolutionary algorithm.
免疫进化算法是在深入理解现有进化算法的基础上，受生物免疫机制的启发而形成的一种新的优化算法。
Immune evolutionary algorithm is a new optimization algorithm inspired by biological immune mechanism based on the deep understanding of the existing evolutionary algorithm.
免疫进化算法是在深入理解现有进化算法的基础上，受生物免疫机制的启发而形成的一种新的优化算法。
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