Motif detection inspired by immune memory / Wilson, W. in Journal of the operational research society (JORS), Vol. 62 N° 2 Special issue (Fevrier 2011)  

Public ISBD [article]  inJournal of the operational research society (JORS) > Vol. 62 N° 2 Special issue (Fevrier 2011) . - pp. 253–265 Titre : Motif detection inspired by immune memory Type de document : texte imprimé Auteurs : Wilson, W., Auteur ; Birkin, P., Auteur ; Aickelin, U., Auteur Année de publication : 2011 Article en page(s) : pp. 253–265 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Heuristics Time series Motif detection Artificial immune systems Immune memory Index. décimale : 001.424 Résumé : The search for patterns or motifs in data represents an area of key interest to many researchers. In this paper we present the motif tracking algorithm (MTA), a novel immune-inspired pattern identification tool that is able to identify variable length unknown motifs that repeat within time series data. The algorithm searches from a neutral perspective that is independent of the data being analysed and the underlying motifs. In this paper we test the flexibility of the MTA by applying it to the search for patterns in two industrial data sets. The algorithm is able to identify a population of meaningful motifs in both cases, and the value of these motifs is discussed. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n2/abs/jors201081a.html [article] Motif detection inspired by immune memory [texte imprimé] / Wilson, W., Auteur ; Birkin, P., Auteur ; Aickelin, U., Auteur . - 2011 . - pp. 253–265. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 2 Special issue (Fevrier 2011) . - pp. 253–265 Mots-clés : Heuristics Time series Motif detection Artificial immune systems Immune memory Index. décimale : 001.424 Résumé : The search for patterns or motifs in data represents an area of key interest to many researchers. In this paper we present the motif tracking algorithm (MTA), a novel immune-inspired pattern identification tool that is able to identify variable length unknown motifs that repeat within time series data. The algorithm searches from a neutral perspective that is independent of the data being analysed and the underlying motifs. In this paper we test the flexibility of the MTA by applying it to the search for patterns in two industrial data sets. The algorithm is able to identify a population of meaningful motifs in both cases, and the value of these motifs is discussed. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n2/abs/jors201081a.html

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