Fuzzy C-means Clustering Applied to the Classification of Glycyrrhiza uralensis Communities in North China
Automation, Control and Intelligent Systems
Volume 5, Issue 5, October 2017, Pages: 73-77
Received: Nov. 16, 2017; Published: Nov. 20, 2017
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Authors
Naiqi Song, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
Jintun Zhang, College of Life Sciences, Beijing Normal University, Beijing, China
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Abstract
Fuzzy C-means clustering is a soft technique and has some advantages in ecological studies. Glycyrrhiza uralensis is an endangered medicinal plant species and mainly distributed in North China. Species data of 100 plots of 5 m x 5 m from semi-arid and arid regions in North China were analyzed by fuzzy C-means clustering. A hundred plots were classified into 12 vegetation formations by fuzzy C-means clustering. These formations were main communities dominated by Glycyrrhiza uralensis in North China. Each formation has its own composition, structure, distribution range and environment, and all of them should be protected effectively. The results suggest that fuzzy C-means clustering is an useful technique for classification of plant community.
Keywords
Fuzzy Set Theory, Numerical Classification, Licorice, Medicinal Plant, Ecological Conservation
To cite this article
Naiqi Song, Jintun Zhang, Fuzzy C-means Clustering Applied to the Classification of Glycyrrhiza uralensis Communities in North China, Automation, Control and Intelligent Systems. Vol. 5, No. 5, 2017, pp. 73-77. doi: 10.11648/j.acis.20170505.13
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