Prediction in Dissolved Oxygen Concentration and Occurrence of Hypoxia Water Mass in Jinhae Bay Based on Machine Learning Model

Abstract

We carried out studies on prediction in concentration of dissolved oxygen (DO) with LSTM model and prediction in occurrence of hypoxia water mass (HWM) with decision tree. As results of study on prediction in DO concentration, a large number of Hidden node caused high complexity of model and required enough Epoch. And it was high accuracy in long Sequence length as prediction time step increased. The results of prediction in occurrence of HWM showed that the accuracy of nonHWM case was 66.1% in 30 day prediction, it was higher than 37.5% of HWM case. The reason is that the decision tree might overestimate DO concentration.