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Novel Implementation of the Artificial Immune System Memory

by Hossam Meshref
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 155 - Number 13
Year of Publication: 2016
Authors: Hossam Meshref
10.5120/ijca2016912585

Hossam Meshref . Novel Implementation of the Artificial Immune System Memory. International Journal of Computer Applications. 155, 13 ( Dec 2016), 36-41. DOI=10.5120/ijca2016912585

@article{ 10.5120/ijca2016912585,
author = { Hossam Meshref },
title = { Novel Implementation of the Artificial Immune System Memory },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 155 },
number = { 13 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 36-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume155/number13/26669-2016912585/ },
doi = { 10.5120/ijca2016912585 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:01:12.076163+05:30
%A Hossam Meshref
%T Novel Implementation of the Artificial Immune System Memory
%J International Journal of Computer Applications
%@ 0975-8887
%V 155
%N 13
%P 36-41
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

During the past decade, there were many approaches that made use of the concepts of artificial immune system. By reviewing the literature, it was found that the research on the artificial immune memory design was sparse and only a few researchers attempted to embark upon issues related to it. This proposed research introduces a novel model that serves as an artificial memory for the artificial immune system. The proposed research design approaches this goal by modeling the primary immune memory response using an idiotopic artificial immune network. As well, the secondary immune memory response is modeled by using a hetero-associative memory network. The two models were tested and the results showed considerable resemblance with the primary and secondary immune memory system behavior. The testing results showed that the developed memory models achieved 100% recognition rates for the tested patterns. Even after adding noise to the input data, the overall memory model showed acceptable recognition rate of 87.5% for 25% noise, and 68.7% recognition rate for 50% noise. Therefore, the designed primary and secondary artificial immune memory model achieve significant potential in representing the behavior of the original immune system memory.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Immune Systems Artificial Immune Memory Idiotopic Artificial Immune Network Hetero-Associative Networks

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