By Topic

Self-organizing feature map clustering based on fuzzy equivalence relation and its application in ecological analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jin-Tun Zhang ; Coll. of Life Sci., Beijing Normal Univ., Beijing, China ; Ming Li

Fuzzy equivalence clustering based on fuzzy set theory and Self organizing feature map (SOFM) clustering based on neural network are both effective methods in ecological studies. They are powerful in analyzing and solving complicated and non-linear matters and for their freedom from restrictive assumptions. The combination of Fuzzy equivalence clustering and SOFM clustering may produce better methodology. This study tried to combine them in a new method, Fuzzy equivalence SOFM clustering, and to apply it in the analysis of plant communities. The dataset was consisted of importance values of 70 species in 30 samples of 10 m × 20 m. First, we calculated fuzzy similarity matrix of samples; second, transforming fuzzy similarity matrix to fuzzy equivalence relation matrix; third, the fuzzy equivalence relation matrix was input to neural network and then SOFM was used to classified samples. The 30 samples were clustered into 5 groups, representing 5 vegetation communities. This classification result was reasonable and ecological meaningful which suggests that fuzzy equivalence SOFM clustering is effective method in ecological study. The fuzzy equivalence SOFM clustering shares both advantages of fuzzy set theory and neural network.

Published in:

Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on  (Volume:2 )

Date of Conference:

26-28 July 2011