免疫克隆扩增模式提取在网络故障诊断中的应用

为了解决网络故障诊断中的模式识别问题，文中从生物免疫系统与网络故障诊断的相似性出发，提出一种基于免疫克隆扩增原理的网络故障诊断方法。该方法模拟生物免疫系统中的克隆、变异、抑制、记忆等特性，通过免疫训练网络故障样本提取网络故障模式，再用最近邻分类原则对故障样本分类。实验结果表明该方法能有效识别网络故障，并且对于未知模式的故障具有一定的泛化性。

Application of Immune Clone Increase Method in Network Fault Diagnosis

In order to solve the problem of mode recognition in network fault diagnosis, this paper, starting form the similarity with biologic immune systems, proposes a new method of network fault diagnosis based on immune clone increase principle. This method simulates the characteristics of biologic immune system, such as clone, mutation, restraint and memory. It extracts the network fault modes from the immunity-trained network fault samples,and then by using the nearest classification categorization criteria, categorizes the network fault samples. Experiment result shows that this method could recognize the network fault effectively. Meanwhile it also has generalization to unknown-mode faults.