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。
A new artificial immune recognition algorithm based on immune recognition principle is proposed in this paper.
人工免疫系统研究中大多借鉴克隆选择原理来构建免疫识别算法。
Currently in the research of artificial immune system, the clonal selection principle is commonly used in designing immune recognition algorithms.
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。
Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is proposed.
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 hybrid RBF training method based on immune algorithm and least square method is proposed and applied in radar antenna scanning-style recognition system.
将数据场理论引入到计算机免疫的研究中，设计了一种识别器的构造方法及其动态识别算法。
A construction method of detector and its relevant dynamic recognition algorithm were put forward by introducing the data field theory to computer immunology.
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。
A Radial Basis Function (RBF) neural network learning algorithm based on immune recognition principle is studied.
在此基础上，模拟生物体的抗原识别、免疫应答等实际免疫行为，提出一种新的人工免疫算法。
Then simulating the antigen identify of organism, immune response and other actual immune behavior, a new artificial immune algorithm is put forward.
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。
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.
为了增强情感识别过程中皮肤电反应(GSR)信号特征选择的有效性，提出了一种改进的模拟退火免疫粒子群算法。
An improved immune particle swarm optimization was presented in this study in order to increase the effectiveness of feature selection for emotion recognition based on Galvanic Skin Response (GSR).
为了增强情感识别过程中皮肤电反应(GSR)信号特征选择的有效性，提出了一种改进的模拟退火免疫粒子群算法。
An improved immune particle swarm optimization was presented in this study in order to increase the effectiveness of feature selection for emotion recognition based on Galvanic Skin Response (GSR).
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