M. Scardi et Lw. Harding, Developing an empirical model of phytoplankton primary production: a neural network case study, ECOL MODEL, 120(2-3), 1999, pp. 213-223
We describe the development of a neural network model for estimating primar
y production of phytoplankton. Data from an enriched estuary in the eastern
United States, Chesapeake Bay, were used to train, validate and test the m
odel. Two error backpropagation multilayer perceptrons were trained: a simp
ler one (3-5-1) and a more complex one (12-5-1). Both neural networks outpe
rformed conventional empirical models, even though only the latter, which e
xploits a larger suite of predictive variables, provided truly accurate out
puts. The application of this neural network model is thoroughly discussed
and the results of a sensitivity analysis are also presented. (C) 1999 Else
vier Science B.V. All rights reserved.