A novel classification method based on artificial immune system and quantum mechanics theory

Ma Liling; Zhao Zhang; Xiaohang Zhou; Junzheng Wang

doi:10.1109/CIS.2009.138

A novel classification method based on artificial immune system and quantum mechanics theory

Ma Liling^*
, Zhao Zhang
, Xiaohang Zhou
, Junzheng Wang

^*Corresponding author for this work

School of Automation

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

Inspired by natural immune systems, Artificial Immune System (AIS) is an emerging kind of computational intelligence paradigm. The traditional immune algorithm and Ai-net for clustering still have the problems of training time-consumption and accuracy. In this paper, AIS Algorithm is improved with Quantum Mechanics theory and the Schrödinger equation to add the idea of the energy level into the immune net. The analysis and simulation data are taken from UCI data. It is proved that the accuracy of the artificial immune system is improved, while gaining better training speed compared with the one with border methods such as SVM at the same degree of precision.

Original language	English
Title of host publication	CIS 2009 - 2009 International Conference on Computational Intelligence and Security
Pages	11-14
Number of pages	4
DOIs	https://doi.org/10.1109/CIS.2009.138
Publication status	Published - 2009
Event	2009 International Conference on Computational Intelligence and Security, CIS 2009 - Beijing, China Duration: 11 Dec 2009 → 14 Dec 2009

Publication series

Name	CIS 2009 - 2009 International Conference on Computational Intelligence and Security
Volume	1

Conference

Conference	2009 International Conference on Computational Intelligence and Security, CIS 2009
Country/Territory	China
City	Beijing
Period	11/12/09 → 14/12/09

Keywords

Artificial immune system
Clustering
Computational intelligence
Energy level
Quantum mechanics theory

Access to Document

10.1109/CIS.2009.138

Cite this

Liling, M., Zhang, Z., Zhou, X., & Wang, J. (2009). A novel classification method based on artificial immune system and quantum mechanics theory. In CIS 2009 - 2009 International Conference on Computational Intelligence and Security (pp. 11-14). Article 5376761 (CIS 2009 - 2009 International Conference on Computational Intelligence and Security; Vol. 1). https://doi.org/10.1109/CIS.2009.138

@inproceedings{eee519baaaa3454bbc3b3799ecdfd9ee,

title = "A novel classification method based on artificial immune system and quantum mechanics theory",

abstract = "Inspired by natural immune systems, Artificial Immune System (AIS) is an emerging kind of computational intelligence paradigm. The traditional immune algorithm and Ai-net for clustering still have the problems of training time-consumption and accuracy. In this paper, AIS Algorithm is improved with Quantum Mechanics theory and the Schr{\"o}dinger equation to add the idea of the energy level into the immune net. The analysis and simulation data are taken from UCI data. It is proved that the accuracy of the artificial immune system is improved, while gaining better training speed compared with the one with border methods such as SVM at the same degree of precision.",

keywords = "Artificial immune system, Clustering, Computational intelligence, Energy level, Quantum mechanics theory",

author = "Ma Liling and Zhao Zhang and Xiaohang Zhou and Junzheng Wang",

year = "2009",

doi = "10.1109/CIS.2009.138",

language = "English",

isbn = "9780769539317",

series = "CIS 2009 - 2009 International Conference on Computational Intelligence and Security",

pages = "11--14",

booktitle = "CIS 2009 - 2009 International Conference on Computational Intelligence and Security",

note = "2009 International Conference on Computational Intelligence and Security, CIS 2009 ; Conference date: 11-12-2009 Through 14-12-2009",

}

Liling, M, Zhang, Z, Zhou, X & Wang, J 2009, A novel classification method based on artificial immune system and quantum mechanics theory. in CIS 2009 - 2009 International Conference on Computational Intelligence and Security., 5376761, CIS 2009 - 2009 International Conference on Computational Intelligence and Security, vol. 1, pp. 11-14, 2009 International Conference on Computational Intelligence and Security, CIS 2009, Beijing, China, 11/12/09. https://doi.org/10.1109/CIS.2009.138

A novel classification method based on artificial immune system and quantum mechanics theory. / Liling, Ma; Zhang, Zhao; Zhou, Xiaohang et al.
CIS 2009 - 2009 International Conference on Computational Intelligence and Security. 2009. p. 11-14 5376761 (CIS 2009 - 2009 International Conference on Computational Intelligence and Security; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A novel classification method based on artificial immune system and quantum mechanics theory

AU - Liling, Ma

AU - Zhang, Zhao

AU - Zhou, Xiaohang

AU - Wang, Junzheng

PY - 2009

Y1 - 2009

N2 - Inspired by natural immune systems, Artificial Immune System (AIS) is an emerging kind of computational intelligence paradigm. The traditional immune algorithm and Ai-net for clustering still have the problems of training time-consumption and accuracy. In this paper, AIS Algorithm is improved with Quantum Mechanics theory and the Schrödinger equation to add the idea of the energy level into the immune net. The analysis and simulation data are taken from UCI data. It is proved that the accuracy of the artificial immune system is improved, while gaining better training speed compared with the one with border methods such as SVM at the same degree of precision.

AB - Inspired by natural immune systems, Artificial Immune System (AIS) is an emerging kind of computational intelligence paradigm. The traditional immune algorithm and Ai-net for clustering still have the problems of training time-consumption and accuracy. In this paper, AIS Algorithm is improved with Quantum Mechanics theory and the Schrödinger equation to add the idea of the energy level into the immune net. The analysis and simulation data are taken from UCI data. It is proved that the accuracy of the artificial immune system is improved, while gaining better training speed compared with the one with border methods such as SVM at the same degree of precision.

KW - Artificial immune system

KW - Clustering

KW - Computational intelligence

KW - Energy level

KW - Quantum mechanics theory

UR - https://www.scopus.com/pages/publications/77949289033

U2 - 10.1109/CIS.2009.138

DO - 10.1109/CIS.2009.138

M3 - Conference contribution

AN - SCOPUS:77949289033

SN - 9780769539317

T3 - CIS 2009 - 2009 International Conference on Computational Intelligence and Security

SP - 11

EP - 14

BT - CIS 2009 - 2009 International Conference on Computational Intelligence and Security

T2 - 2009 International Conference on Computational Intelligence and Security, CIS 2009

Y2 - 11 December 2009 through 14 December 2009

ER -

A novel classification method based on artificial immune system and quantum mechanics theory

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Keywords

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