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https://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 |
Appears in Collections: | Aurora harvest Earth and Environmental Sciences publications Environment Institute publications |
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