Author(s)

M. French & F. Recknagel

Abstract

Modeling of algal blooms in freshwaters using artificial neural networks M. French* & F. Recknagel& "Department of Civil Engineering, University of Louisville, ^Department of Environmental Science, University of Adelaide, Roseworthy, S.A. 5371, Australia Abstract The development of a neural network model for predicting algal blooms is described. The neural network consists of a 3 layer structure with input, hidden, and output layers. Training is conducted using back-propagation where the data are presented as a series of learning sets such that the inputs are observable water quality parameters and outputs are the biomass quantities of specific algal groups. Training is conducted using three years of daily values of water quality parameters and validation is performed using two years of independent daily values to predict the magnitude and timing of blooms of 7 different algae groups with a lead time of 1 day using only the current day water quality parameters. The water

Keywords