Earticle

초록

영어

This paper proposes a fast immune recognition model based on immune response. Inspired by biological immune system, AIS for anomaly detection has been adopted widely because of its analogy with body resistance in the immune system provided against agents which causes diseases. This paper mainly studies correspondence between immune response and anomaly detection. Compared with traditional AIS, the change of antigen type is judged by statistical techniques, which ignores the differences of the different systems. Antibody recognition is initiated by the proposed model only when the type of antigen has changed, which improves the efficiency of the algorithm. Complexity analysis shows the proposed algorithm is a linear algorithm. The usefulness of the proposed model is demonstrated through experiments. The experiments illustrate the availability and feasibility of the model.

목차

Abstract
 1. Introduction
 2. Related Work
  2.1. Immunological Recognition Models and Theories
  2.2. Immune Response
 3. Fast Immune Recognition Model based on Immune Response
 4. Key Issues of FIRM
  4.1. Antigen Evaluation
  4.2. Antibody Recognition
  4.3. Antibody Evolution
  4.4. Fast Immune Recognition Algorithm based on Immune Response
 5. Experiments
  5.1. Breast Cancer Dataset
  5.2. Iris Dataset
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Yuan Tao [ Computation Center, Shanghai University, Shanghai 200444, China ]
• Min Hu [ SILC Business School, Shanghai University, Shanghai 201800, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605