The use of the hyperbolic smoothing clustering algorithm in taxonomy of macroalgae
RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 4, pp. 735-751.

This work proposes a new methodological approach for grouping data in taxonomy. Macroalgae of the genus Caulerpa were selected as a study model on basis of their remarkable morphological plasticity, and of the difficulty in identifying those algae using the traditional systematical methods. The results obtained from the application of the hyperbolic smoothing algorithm demonstrate the feasibility of its use in biological taxonomy. The new methodology herein proposed may be used isolatedly or in association with other methodologies already proven, not only in phycology, but also in other areas of biology.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2015002
Classification : 92-XX, 92B10
Mots clés : Hyperbolic smoothing, biological taxonomy, macroalgae
Sousa Batista, Maria Gardênia 1 ; de Lima, Francisca Lúcia 1 ; Santana, André Macedo 2 ; Xavier, Adilson Elias 3

1 State University Piauí – UESPI, Brazil
2 Federal University of Piauí – UFPI, Brazil
3 Federal University of Rio de Janeiro – UFRJ, Brazil
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     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
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Sousa Batista, Maria Gardênia; de Lima, Francisca Lúcia; Santana, André Macedo; Xavier, Adilson Elias. The use of the hyperbolic smoothing clustering algorithm in taxonomy of macroalgae. RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 4, pp. 735-751. doi : 10.1051/ro/2015002. http://www.numdam.org/articles/10.1051/ro/2015002/

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