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Selforganizology, 2014, 1(1): 8-15
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Article

Invertebrate diversity classification using self-organizing map neural network: with some special topological functions

WenJun Zhang1,2, QuHuan Li1
1School of Life Sciences, Sun Yat-sen University, Guangzhou, China
2International Academy of Ecology and Environmental Sciences, Hong Kong

Received 16 March 2014;Accepted 10 April 2014;Published online 1 June 2014
IAEES

Abstract
In present study we used self-organizing map (SOM) neural network to conduct the non-supervisory clustering of invertebrate orders in rice field. Four topological functions, i.e., cossintopf, sincostopf, acossintopf, and expsintopf, established on the template in toolbox of Matlab, were used in SOM neural network learning. Results showed that clusters were different when using different topological functions because different topological functions will generate different spatial structure of neurons in neural network. We may chose these functions and results based on comparison with the practical situation.

Keywords self-organizing map (SOM) neural network;topological functions;Matlab;cluster analysis;invertebrates.


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