Immune detection algorithms are an important part of research of artificial immune system.
仿生物免疫检测算法是人工免疫系统研究的一个重要的组成部分。
On the other hand, the artificial immune system in data mining mainly adopts the basic immune algorithms, which ignore the unique characters of the other immune mechanisms such as the immune networks.
目前对于基于人工免疫系统的数据挖掘技术的研究，多使用的是基本的免疫算法，而忽略了免疫网络模型等其它免疫机理所具有的独特优势。
Currently in the research of artificial immune system, the clonal selection principle is commonly used in designing immune recognition algorithms.
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。
Artificial immune Clone Selection algorithm is a novel algorithm which was inspired by the biological immune system. And it has become a new member of the family of intelligent algorithms.
人工免疫克隆选择算法是受生物免疫系统启示而设计的新型算法，它已经成为智能计算大家庭的新成员。
Such algorithms include evolutionary algorithm (EA), particle swarm optimization (PSO), artificial immune system (AIS) and ant colony optimization (ACO) and so on.
这类算法主要包括进化算法(EA)、粒子群算法(PSO)、人工免疫系统(ais)和蚁群算法(aco)等等。
Such algorithms include evolutionary algorithm (EA), particle swarm optimization (PSO), artificial immune system (AIS) and ant colony optimization (ACO) and so on.
这类算法主要包括进化算法(EA)、粒子群算法(PSO)、人工免疫系统(ais)和蚁群算法(aco)等等。
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