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https://hdl.handle.net/2440/27266
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Type: | Journal article |
Title: | Applications of machine learning to ecological modelling |
Author: | Recknagel, F. |
Citation: | Ecological Modelling, 2001; 146(1-3):303-310 |
Publisher: | Elsevier Science BV |
Issue Date: | 2001 |
ISSN: | 0304-3800 1872-7026 |
Abstract: | The paper provides a summary of paper presentations at the 2nd International Conference on Applications of Machine Learning to Ecological Modelling and a preview of forthcoming developments in this area. Artificial neural networks were demonstrated to be very useful for nonlinear ordination and visualization of ecological data by Kohonen networks, and ecological time-series modelling by recurrent networks. Genetic algorithms proved to be very innovative for hybridizing deductive models, and evolving predictive rules, process equations and parameters. Newly emerging adaptive agents provide a novel framework for the discovery and forecasting of emergent ecosystem structures and behaviours in response to environmental changes. © 2001 Elsevier Science B.V. All rights reserved. |
DOI: | 10.1016/S0304-3800(01)00316-7 |
Published version: | http://dx.doi.org/10.1016/s0304-3800(01)00316-7 |
Appears in Collections: | Aurora harvest 6 Environment Institute publications Soil and Land Systems publications |
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