A new artificial immune recognition algorithm based on immune recognition principle is proposed in this paper.
本文基于免疫识别原理提出了一种新型人工免疫识别算法。
Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
A hybrid RBF training method based on immune algorithm and least square method is proposed and applied in radar antenna scanning-style recognition system.
采用一种基于免疫算法和最小二乘法的两级学习方法设计径向基函数（RBF）网络，并将其应用于雷达天线扫描方式识别系统。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is studied.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
提出了一种基于免疫识别原理的径向基函数神经网络学习算法。
We design and implement the artificial immune network algorithm, and successfully apply this algorithm in solving a pattern recognition problem and a data clustering problem.
在此基础上，设计和实现了人工免疫网络算法，并应用该算法成功解决了一个模式识别和数据聚类问题。
In this paper, an immune clustering algorithm is presented, which includes antibody production, antigen recognition, and antibody optimization.
提出了一种免疫聚类算法，该算法主要包括抗体产生、抗原识别和抗体优化等过程。
In this paper, an immune clustering algorithm is presented, which includes antibody production, antigen recognition, and antibody optimization.
提出了一种免疫聚类算法，该算法主要包括抗体产生、抗原识别和抗体优化等过程。
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