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
Cathay General Hospital, No. 280, Section 4, Ren-Ai Road, Da-An District, Taipei, Taiwan


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© 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.

* Address correspondence to this author at the Department of Computer Science and Information Engineering, National Central University, No. 300, Jung-da Road, Chung-li, Tao-yuan, Taiwan 320; Tel: (886-3) 422-7151, Ext. 34500; Fax: (886-3) 422-2681; E-mail:muchun@csie.ncu.edu.tw


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.