Special issue: Applications of machine learning to ecological modelling - Preface

被引:9
|
作者
Recknagel, F [1 ]
机构
[1] Univ Adelaide, Dept Soil & Water, ISEI, Glen Osmond, SA 5064, Australia
关键词
Adaptive agents; Artificial neural network; Ecological modelling; Genetic algorithm; Knowledge discovery; Machine learning; Model hybridization; Multivariate statistics; Time-series modelling;
D O I
10.1016/S0304-3800(01)00291-5
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
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.
引用
收藏
页码:1 / 2
页数:2
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