Abstract
The use of artificial neuronal networks (ANNs) to model environmental problems is increasing. They have been used to model systems as diverse as algal distributions in oceans (Simpson et al. 1992), grassland community changes (Tan and Smeins 1996), and in the recognition of birdsong (McIlraith and Card 1997). They are well suited to modelling complex nonlinear systems which are inherently ‘noisy,’ a characteristic that makes them suited to modelling environmental systems. They have been used in studies in this and related papers, to model environmental influences on the impact of tropospheric ozone pollution on plants (Balls et al. 1995; Balls et al. 1996; Roadknight et al. 1997; Ball et al. 1998).
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Ball, G.R., Palmer-Brown, D., Mills, G.E. (2000). A Comparison of Artificial Neuronal Network and Conventional Statistical Techniques for Analysing Environmental Data. In: Lek, S., Guégan, JF. (eds) Artificial Neuronal Networks. Environmental Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-57030-8_12
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DOI: https://doi.org/10.1007/978-3-642-57030-8_12
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