Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/58955
Type: Journal article
Title: Comparison of a self organising map and simple evolving connectionist system for predicting insect pest establishment
Author: Watts, M.
Worner, S.
Citation: International Journal of Information Technology, 2006; 12(6):35-42
Publisher: International Academy of Sciences
Issue Date: 2006
ISSN: 1305-239X
0218-7957
Statement of
Responsibility: 
Watts, M.J. and Worner, S.P
Abstract: A comparison of two artificial neural network methods for predicting the risk of insect pest species establishment in regions where they are not normally found is presented. The ANN methods include a well-known unsupervised learning algorithm and a relatively new supervised constructive method. A New Zealand pest species assemblage as an example was used to compare model predictions. Both methods gave similar results for already established and non-established species.
Keywords: Self-Organising Maps; Evolving Connectionist Systems; pest invasion prediction
Rights: (C) Singapore computer society 2006
RMID: 0020103739
Appears in Collections:Earth and Environmental Sciences publications
Environment Institute publications

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