Modelling and prediction of phytoplankton growth with equation discovery

In contrast with traditional modelling methods, which are used to identify parameter values of a model with known structure, equation discovery system s identify the structure of the model also. The model generated with such s ystems can give experts a better insight into the measured data and can be also used for predicting future values of the measured variables. This pape r presents LAGRAMGE, an equation discovery system that allows the user to d efine the space of possible model structures and to make use of domain spec ific expert knowledge in the form of function definitions. We use LAGRAMGE to automate the modelling of phytoplankton growth in lake Glumsoe, Denmark, The structure of the model constructed with LAGRAMGE agrees with human exp erts' expectations. The model can be successfully used for long term predic tion of phytoplankton concentration during algal blooms. (C) 1998 Elsevier Science B.V. All rights reserved.