Application of the clonal selection algorithm in artificial immune systems for shape recognition

Norulhidayah Isa; Norlina Mohd Sabri; Ku Shairah Jazahanim; Nicholas K. Taylor

doi:10.1109/INFRKM.2010.5466915

Application of the clonal selection algorithm in artificial immune systems for shape recognition

Norulhidayah Isa, Norlina Mohd Sabri, Ku Shairah Jazahanim, Nicholas K. Taylor

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

8 Citations (Scopus)

Abstract

Artificial Immune Systems (AISs) emerged in 1990s. The capability of AISs for learning new information, recalling what has been learned and recognizing a decentralized pattern are reasons why numerous models have been developed, implemented and used in various types of problems. This paper describes the implementation of AISs in solving an image classification problem. The Clonal Selection Algorithm has been chosen to evolve solutions in the form of antibodies during the recognizing process. In this approach, three types of shape were treated as antigens. Two experiments have been undertaken and the results show that the algorithm can perform with an accuracy of up to 95%. As a conclusion, the study showed that the Clonal Selection Algorithm can be applied to shape recognition problems. ©2010 IEEE.

Original language	English
Title of host publication	Proceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10
Pages	223-228
Number of pages	6
DOIs	https://doi.org/10.1109/INFRKM.2010.5466915
Publication status	Published - 2010
Event	International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10 - Shah Alam, Malaysia Duration: 17 Mar 2010 → 18 Mar 2010

Conference

Conference	International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10
Country/Territory	Malaysia
City	Shah Alam
Period	17/03/10 → 18/03/10

Keywords

AIS
Artificial immune system
Clonal selection
CLONALG
Recognition
Shape classification

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10.1109/INFRKM.2010.5466915

Cite this

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title = "Application of the clonal selection algorithm in artificial immune systems for shape recognition",

abstract = "Artificial Immune Systems (AISs) emerged in 1990s. The capability of AISs for learning new information, recalling what has been learned and recognizing a decentralized pattern are reasons why numerous models have been developed, implemented and used in various types of problems. This paper describes the implementation of AISs in solving an image classification problem. The Clonal Selection Algorithm has been chosen to evolve solutions in the form of antibodies during the recognizing process. In this approach, three types of shape were treated as antigens. Two experiments have been undertaken and the results show that the algorithm can perform with an accuracy of up to 95%. As a conclusion, the study showed that the Clonal Selection Algorithm can be applied to shape recognition problems. {\textcopyright}2010 IEEE.",

keywords = "AIS, Artificial immune system, Clonal selection, CLONALG, Recognition, Shape classification",

author = "Norulhidayah Isa and Sabri, {Norlina Mohd} and Jazahanim, {Ku Shairah} and Taylor, {Nicholas K.}",

year = "2010",

doi = "10.1109/INFRKM.2010.5466915",

language = "English",

isbn = "9781424456512",

pages = "223--228",

booktitle = "Proceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10",

note = "International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10 ; Conference date: 17-03-2010 Through 18-03-2010",

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Isa, N, Sabri, NM, Jazahanim, KS & Taylor, NK 2010, Application of the clonal selection algorithm in artificial immune systems for shape recognition. in Proceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10. pp. 223-228, International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10, Shah Alam, Malaysia, 17/03/10. https://doi.org/10.1109/INFRKM.2010.5466915

Application of the clonal selection algorithm in artificial immune systems for shape recognition. / Isa, Norulhidayah; Sabri, Norlina Mohd; Jazahanim, Ku Shairah et al.

Proceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10. 2010. p. 223-228.

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

TY - GEN

T1 - Application of the clonal selection algorithm in artificial immune systems for shape recognition

AU - Isa, Norulhidayah

AU - Sabri, Norlina Mohd

AU - Jazahanim, Ku Shairah

AU - Taylor, Nicholas K.

PY - 2010

Y1 - 2010

N2 - Artificial Immune Systems (AISs) emerged in 1990s. The capability of AISs for learning new information, recalling what has been learned and recognizing a decentralized pattern are reasons why numerous models have been developed, implemented and used in various types of problems. This paper describes the implementation of AISs in solving an image classification problem. The Clonal Selection Algorithm has been chosen to evolve solutions in the form of antibodies during the recognizing process. In this approach, three types of shape were treated as antigens. Two experiments have been undertaken and the results show that the algorithm can perform with an accuracy of up to 95%. As a conclusion, the study showed that the Clonal Selection Algorithm can be applied to shape recognition problems. ©2010 IEEE.

AB - Artificial Immune Systems (AISs) emerged in 1990s. The capability of AISs for learning new information, recalling what has been learned and recognizing a decentralized pattern are reasons why numerous models have been developed, implemented and used in various types of problems. This paper describes the implementation of AISs in solving an image classification problem. The Clonal Selection Algorithm has been chosen to evolve solutions in the form of antibodies during the recognizing process. In this approach, three types of shape were treated as antigens. Two experiments have been undertaken and the results show that the algorithm can perform with an accuracy of up to 95%. As a conclusion, the study showed that the Clonal Selection Algorithm can be applied to shape recognition problems. ©2010 IEEE.

KW - AIS

KW - Artificial immune system

KW - Clonal selection

KW - CLONALG

KW - Recognition

KW - Shape classification

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DO - 10.1109/INFRKM.2010.5466915

M3 - Conference contribution

SN - 9781424456512

SP - 223

EP - 228

BT - Proceedings - 2010 International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10

T2 - International Conference on Information Retrieval and Knowledge Management: Exploring the Invisible World, CAMP'10

Y2 - 17 March 2010 through 18 March 2010

ER -

Application of the clonal selection algorithm in artificial immune systems for shape recognition

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