Artificial neural network modeling of algal bloom in Xiangxi Bay of Three Gorges Reservoir

Algal bloom model in Xiangxi Bay of Three Gorges Reservoir was established by artificial neural network (ANN) technology. Using stepwise multiple linear regression method, the important environmental factors (dissolved oxygen, pH, total nitrogen, ammonium nitrogen and silicate) were selected as input variables in ANN model. The optimal structure of the ANN model was determined based on leave one out cross validation. The squared correlation coefficient R
²
, squared correlation coefficient in cross validation Q
²
and predictive squared correlation coefficient R
²
_pred
of the optimal ANN model are 0.8267, 0.7460 and 0.7522, respectively. The ANN model has been shown to perform well for simulating the algal bloom in Xiangxi Bay.