RESEARCH ARTICLE
A New Approach to Artificial Immune Systems and its Application in Constructing On-line Learning Neuro-Fuzzy Systems
Mu-Chun Su1, Po-Chun Wang 2, Yuan-Shao Yang 1
Department of Computer Science and Information Engineering, National Central University, No. 300, Jung-da Road, Chung-li, Tao-yuan, Taiwan 320
Article Information
Identifiers and Pagination:
Year: 2008Volume: 2
First Page: 1
Last Page: 10
Publisher Id: TOAIJ-2-1
DOI: 10.2174/1874061800802010001
Article History:
Electronic publication date: 27/3/2008Collection year: 2008
© 2017 Su et al.;
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
In this paper, we present an on-line learning neuro-fuzzy system which was inspired by parts of the mechanisms in immune systems. It illustrates how an on-line learning neuro-fuzzy system can capture the basic elements of the immune system and exhibit some of its appealing properties. During the learning procedure, a neuro-fuzzy system can be incrementally constructed. We illustrate the potential of the on-line learning neuro-fuzzy system on several benchmark classification problems and function approximation problems.
Keywords: Artificial immune systems, on-line learning, neural networks, fuzzy systems.
