The use of the hyperbolic smoothing clustering algorithm in taxonomy of macroalgae
| Autor: | Francisca Lúcia de Lima, Adilson Elias Xavier, Andre M. Santana, Maria Gardenia Sousa Batista |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Mathematical optimization
business.industry Management Science and Operations Research Machine learning computer.software_genre Computer Science Applications Theoretical Computer Science Taxonomy (biology) Artificial intelligence Biological taxonomy Cluster analysis business computer Smoothing Mathematics |
| Zdroj: | RAIRO - Operations Research. 49:735-751 |
| ISSN: | 1290-3868 0399-0559 |
| DOI: | 10.1051/ro/2015002 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|