An Algorithm to Generate Detectors in Negative Selection Model

WU Zuo-shun; DOU Wen-hua; ZHU Xiao-jun

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An Algorithm to Generate Detectors in Negative Selection Model

更新时间：2025-07-16

- An Algorithm to Generate Detectors in Negative Selection Model
- Acta Electronica Sinica Vol. 31, Issue 5, Pages: 687-689(2003)
- 作者机构：
  
  国防科技大学计算机学院,湖南,长沙,410073
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393.08
- Published：2003
- 稿件说明：
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WU Zuo-shun, DOU Wen-hua, ZHU Xiao-jun. An Algorithm to Generate Detectors in Negative Selection Model[J]. Acta Electronica Sinica, 2003, 31(5): 687-689.
DOI：

WU Zuo-shun, DOU Wen-hua, ZHU Xiao-jun. An Algorithm to Generate Detectors in Negative Selection Model[J]. Acta Electronica Sinica, 2003, 31(5): 687-689. DOI：

摘要

在介绍人工免疫系统基本概念的基础上

讨论了人工免疫系统中应用广泛的负选择模型.研究的重点是负选择模型中初始检测器集的生成算法

在穷举法的基础上提出了一个新的检测器生成算法

包括算法的设计、性能分析和试验.理论分析与试验结果表明

新生成算法的时间复杂度小于穷举法

随检测器规模成线性递增.在所生成检测器集的性能上新算法也优于穷举法.

Abstract

The Artificial Immune System (AIS) inspired by the natural immune system is introduced.Based on exhaustive algorithm

a new algorithm is presented as detectors generating method in the negative selection model

including its design

performance analysis and experiment.Both mathematical analysis and experiment show that the algorithm runs in time linearly with the size of the detector set.The new algorithm can possibly generate a more powerful detector set than exhaustive algorithm.

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A Cutting Based Detector Generating and Matching Algorithm

An Immune Memory Clone Algorithm for Constrained Multi-Objective Optimization

Development and Prospect of the Artificial Immune System

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