Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, S | - |
dc.contributor.author | Kim, E | - |
dc.contributor.author | Song, E | - |
dc.contributor.author | Park, M | - |
dc.date.accessioned | 2024-01-21T05:01:20Z | - |
dc.date.available | 2024-01-21T05:01:20Z | - |
dc.date.created | 2021-09-04 | - |
dc.date.issued | 2005-06 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://pubs.kist.re.kr/handle/201004/136423 | - |
dc.description.abstract | A novel immunotronic approach to fault detection in hardware based on symbiotic evolution is proposed in this paper. In the immunotronic system, the generation of tolerance conditions corresponds to the generation of antibodies in the biological immune system. In this paper, the principle of antibody diversity, one of the most important concepts in the biological immune system, is employed and it is realized through symbiotic evolution. Symbiotic evolution imitates the generation of antibodies in the biological immune system more than the standard genetic algorithm(SCA) does. It is demonstrated that the suggested method outperforms the previous immunotronic methods with less running time. The suggested method is applied to fault detection in a decade counter (typical example of finite state machines) and MCNC finite state machines and its effectiveness is demonstrated by the computer simulation. | - |
dc.language | English | - |
dc.publisher | SPRINGER-VERLAG BERLIN | - |
dc.subject | TOLERANCE | - |
dc.title | A new immunotronic approach to hardware fault detection using symbiotic evolution | - |
dc.type | Article | - |
dc.description.journalClass | 1 | - |
dc.identifier.bibliographicCitation | ARTIFICIAL INTELLIGENCE AND KNOWLEDGE ENGINEERING APPLICATIONS: A BIOINSPIRED APPROACH, PT 2, PROCEEDINGS, v.3562, pp.133 - 142 | - |
dc.citation.title | ARTIFICIAL INTELLIGENCE AND KNOWLEDGE ENGINEERING APPLICATIONS: A BIOINSPIRED APPROACH, PT 2, PROCEEDINGS | - |
dc.citation.volume | 3562 | - |
dc.citation.startPage | 133 | - |
dc.citation.endPage | 142 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.identifier.wosid | 000230386700014 | - |
dc.identifier.scopusid | 2-s2.0-26444432310 | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.subject.keywordPlus | TOLERANCE | - |
dc.subject.keywordAuthor | immunotronic system | - |
dc.subject.keywordAuthor | hardware fault detection | - |
dc.subject.keywordAuthor | tolerance conditions | - |
dc.subject.keywordAuthor | antibody diversity | - |
dc.subject.keywordAuthor | symbiotic evolution | - |
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