Korea: explanations based on evolutionary computation

1. An ecological model was developed using genetic programming (GP) to predict the time-series dynamics of the diatom, Stephanodiscus hantzschii for the lower Nakdong River, South Korea. Eight years of weekly data showed the river to be hypertrophic (chl. a, 45.1 ± 4.19 lg L)1, mean ± SE, n 427), and S. hantzschii annually formed blooms during the winter to spring flow period (late November to March). 2. A simple non-linear equation was created to produce a 3-day sequential forecast of the species biovolume, by means of time series optimization genetic programming (TSOGP). Training data were used in conjunction with a GP algorithm utilizing 7 years of limnological variables (1995–2001). The model was validated by comparing its output with measurements for a specific year with severe blooms (1994). The model accurately predicted timing of the blooms although it slightly underestimated biovolume (training r2 0.70, test r2 0.78). The model consisted of the following variables: dam discharge and storage, water temperature, Secchi transparency, dissolved oxygen (DO), pH, evaporation and silica concentration. 3. The application of a five-way cross-validation test suggested that GP was capable o